WEB-BASED PLATFORM FOR MANAGING IMAGE BIOMARKERS PDF

12 août 2019 Figure 2 presents the most common promotion channels used by the top-100 projects on. GitHub. The most common channel is Twitter which is used ...

Using JavaScript Frameworks when developing for Zebra Mobile

1 oct. 2019 Example: Angular 2 todoMVC: https://github.com/tastejs/todomvc/tree/master/examples/angular2. – cd angular2. – npm i (install prerequisites).

angular-in-action.pdf

cycle for new features and deprecations. The book examples are written to work with. Angular 5 and above and going forward

CHARACTERIZING AND PREDICTING THE POPULARITY OF

Figure 1.3 shows the GitHub stars history of AngularJS React

Deep-Dive MSAL React

18 août 2022 Deep dive on using MSAL.js to ... OAuth 2.0 Authorization Code Grant with Proof Key for Code ... github.com/derisen/msal-angular-demo.

EntreCom4All–Open resources for entrepreneurship competences

Angular. 21. 4.2.2. Material Design and Angular Material This project aims to facilitate access to open entrepreneurial resources to.

Whats in a GitHub Star? Understanding Repository Starring

10 sept. 2018 result it is common to see projects competing for the same users. For example

Point Clouds Registration with Probabilistic Data Association

example to merge maps produced by different sensors

WEB-BASED PLATFORM FOR MANAGING IMAGE BIOMARKERS

The deliverables of this project are a relational data model 2.3.5 GitHub . ... 3.1.2 Transforming a CSV file into database entities .

Influence analysis of Github repositories

In Github projects have evolved into repositories. 2. We proposed a HITS based repository influence analysis

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 1

Student : Nghi Tran

Professor : Adrien Depeursinge

WEB-BASED PLATFORM FOR

MANAGING IMAGE BIOMARKERS

August 2020

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 2

ABSTRACT

The aim of this paper is to describe the process of implementing a web-based platform to manage image biomarkers, with a focus on managing and sorting datasets for machine learning. The paper will first discuss about the emerging field of radiomics, the need for a comprehensive way to manage large datasets of image biomarkers, and the current solutions in the field. This part will be the foundation for the development of this platform. During the first part, the paper will also solutions, along with a justification of technologies used. This thesis project aim to develop a web platform to manage sets of quantitative image biomarkers. While solutions to extract these biomarkers have been developed, efficiently storing and managing the extracted data is a challenge.

The project will implement a full stack solution from database, to server to front end application. It

transforms extracted image biomarker sets into an interactive web interface for data viewing, exporting, and management.

The deliverables of this project are a relational data model, a back end application with ETL and API

functionalities, and a web application. The result of this project demonstrates that managing quantitative image biomarkers using relational entity model is feasible, but there is still room for improvement. Keywords: Healthcare, Radiomics, Data management, Data modelling, ETL, Web

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 3

FOREWORD

Information Technology at HES-SO Valais-Wallis. The thesis was given by professor Adrien Depeursinge and guided by him along with Roger Schaer and Orfeas Aidonopoulos. project with the goal of developing infrastructure for national image-based personalized medicine. Development of the thesis project spanned from February 2020 to July 2020 in Sierre, Switzerland and later in Helsinki, Finland. The project aims to deliver a working demonstration of the goals provided. I would like to thank Adrien Depeursinge, Roger Schaer, and Orfeas Aidonopoulos for their guidance in the making of this thesis, and Catherine Tacchini and Isabelle Fournier for helping me coordinate remote work when I moved back to Helsinki.

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 4

ABSTRACT ............................................................................................................................................... 2

FOREWORD ............................................................................................................................................. 3

TABLE OF CONTENTS .............................................................................................................................. 4

TABLE OF FIGURES .................................................................................................................................. 7

ABBREVIATIONS ..................................................................................................................................... 9

1. INTRODUCTION AND STATE OF THE ART .................................................................................... 10

1.1 The field of radiomics ................................................................................................................. 10

1.1.1 Biomarkers and features ...................................................................................................... 10

1.2 State of the art ........................................................................................................................... 10

1.2.1 General workflow of radiomics research ............................................................................. 10

1.2.2 Existing radiomics solutions ................................................................................................. 11

1.2.2.1 I2b2 ............................................................................................................................... 11

1.2.2.2 Radiomics Enabler ......................................................................................................... 13

1.2.3 Breaking down the workflow ............................................................................................... 13

1.2.4 Existing specialized products/libraries ................................................................................. 14

1.2.4.1 Kheops ........................................................................................................................... 14

1.2.4.2 Pyradiomics ................................................................................................................... 14

1.2.4.3 Scikit-learn .................................................................................................................... 15

1.3 Role and aim of this project ....................................................................................................... 15

2. METHODOLOGY ............................................................................................................................ 16

2.1 Designing the feature manager ................................................................................................. 16

2.1.1 Introduction to terminologies used ..................................................................................... 16

2.1.2 Use cases .............................................................................................................................. 16

2.1.3 Solution overview ................................................................................................................ 17

2.2 Technologies chosen .................................................................................................................. 18

2.2.1 Database .............................................................................................................................. 18

2.2.1.1 MySQL ........................................................................................................................... 18

2.2.2 Back-end + API ..................................................................................................................... 19

2.2.2.1 Flask .............................................................................................................................. 19

2.2.2.2 Pandas ........................................................................................................................... 19

2.2.2.3 SQLAlchemy .................................................................................................................. 19

2.2.3 Front-end ............................................................................................................................. 20

2.2.3.1 React ............................................................................................................................. 20

2.2.3 Architecture of project ......................................................................................................... 20

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 5

2.2.5 Technologies comparison .................................................................................................... 21

2.3 Tools used ................................................................................................................................... 21

2.3.1 Amazon Relational Database Service ................................................................................... 21

2.3.2 Local MySQL server .............................................................................................................. 23

2.3.3 DBeaver ................................................................................................................................ 23

2.3.4 Visual Studio Code ............................................................................................................... 24

2.3.5 GitHub .................................................................................................................................. 25

3. RESULTS ........................................................................................................................................ 26

3.1 Database ..................................................................................................................................... 26

3.1.1 Data model ........................................................................................................................... 26

3.1.2 Transforming a CSV file into database entities .................................................................... 27

3.1.2.1 CSV file input ................................................................................................................. 27

3.1.2.2 Steps of loading data into the database: ...................................................................... 28

3.1.3 Order of insertion................................................................................................................. 28

3.2 Back-end ..................................................................................................................................... 29

3.2.1 Defining the database schema with SQLAlchemy ............................................................... 29

3.2.2 ETL process ........................................................................................................................... 30

3.2.2.1 Loading raw feature sets ............................................................................................... 30

3.2.2.2 Loading custom QIB ...................................................................................................... 33

3.2.3 REST API endpoints .............................................................................................................. 34

3.2.3.1 Editing patient information (*) ..................................................................................... 35

3.2.3.2 Converting list of QIBFeatures into a table (**)............................................................ 35

3.2.3.3 Converting list of QIBFeatures into a scatterplot (***) ................................................ 36

3.3 Front-end .................................................................................................................................... 37

3.3.1 Dark mode ............................................................................................................................ 37

3.3.2 Grid View .............................................................................................................................. 38

3.3.2.1 Sorting QIBS .................................................................................................................. 38

3.3.2.2 Managing QIBs .............................................................................................................. 38

3.3.2.3 QIB Table view .............................................................................................................. 39

Sorting ................................................................................................................................... 39

Filtering ................................................................................................................................. 39

Pagination ............................................................................................................................. 40

Editing ................................................................................................................................... 40

Column tagging ..................................................................................................................... 40

Exporting ............................................................................................................................... 40

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 6

3.3.2.4 Uploading QIBs .............................................................................................................. 41

3.3.3 Plot View .............................................................................................................................. 42

3.3.3.1 Statistics ........................................................................................................................ 42

3.3.3.2 Generating a bivariate scatterplot ................................................................................ 42

3.3.4 Database View ..................................................................................................................... 43

3.3.4.1 Album ............................................................................................................................ 43

3.3.4.2 Patient ........................................................................................................................... 43

3.3.4.3 Modality & Region ........................................................................................................ 44

3.3.4.4 Feature & Feature Family ............................................................................................. 45

4. DISCUSSION .................................................................................................................................. 46

4.1 Goal evaluation .......................................................................................................................... 46

4.1.1 Storing extracted feature sets ............................................................................................. 46

4.1.2 Providing interface to query and interactively compile feature sets in real time ............... 46

4.1.3 Editing metadata of feature sets without compromising data integrity ............................. 46

4.1.4 Visualization of feature sets ................................................................................................. 47

4.2 Advantages of a modular radiomics solution ............................................................................ 47

4.3 Values added .............................................................................................................................. 48

4.4 Points of improvement .............................................................................................................. 48

4.4.1 Data model ........................................................................................................................... 48

4.4.2 Back-end............................................................................................................................... 49

4.4.3 Front-end ............................................................................................................................. 49

4.4.4 Visualization ......................................................................................................................... 49

4.4.5 Security ................................................................................................................................ 49

5. CONCLUSION ................................................................................................................................ 50

REFERENCES .......................................................................................................................................... 51

APPENDIX I PRODUCT BACKLOG .......................................................................................................... 52

APPENDIX II TECHNICAL GUIDE ........................................................................................................... 54

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 7

TABLE OF FIGURES

Figure 1-1 Example of a star schema model ......................................................................................... 11

Figure 1-2 A sample request ................................................................................................................. 12

Figure 1-3 i2b2 web client interface ..................................................................................................... 12

Figure 1-4. Radiomics Enabler interface ............................................................................................... 13

Figure 1-5 Radiomics workflow by stage and technologies .................................................................. 13

Figure 1-6 Kheops web UI and image viewer ....................................................................................... 14

Figure 2-1 Use case diagram ................................................................................................................. 17

Figure 2-2 General architecture of the feature manager ..................................................................... 18

Figure 2-3 Online AWS RDS dashboard ................................................................................................. 19

Figure 2-4 Detailed project architecture ............................................................................................... 21

Figure 2-5 Comparison table of i2b2 and this application technologies .............................................. 21

Figure 2-6 db.t2.micro specifications compared to other general instances ....................................... 22

Figure 2-7 Write/Read IOP (input/output operations per second) from 27th June to 1st July ............ 22

Figure 2-9 DBeaver GUI, with ER Diagram view and Dashboard enabled ............................................ 24

Figure 2-10 List of extensions used over the course of this project's development ............................ 24

Figure 3-1 Example of a feature set extraction file ............................................................................... 27

Figure 3-2 Outcome CSV file ................................................................................................................. 28

Figure 3-3 Order of inserting QIBFeature ............................................................................................. 28

Figure 3-4 Defining Feature table ......................................................................................................... 29

Figure 3-5 Defining Outcome table ....................................................................................................... 29

Figure 3-6 Defining QIBFeature relationships ....................................................................................... 30

Figure 3-7 Steps of loading raw QIBs .................................................................................................... 30

Figure 3-8 A feature set with valid columns ......................................................................................... 30

Figure 3-9 Adding modalities ................................................................................................................ 31

Figure 3-10 Red: hardcoded, Green: used as patient id in Outcome table, Blue: extraction date, not

used ....................................................................................................................................................... 31

Figure 3-11 Random selection using offset .......................................................................................... 32

Figure 3-12 Linking Series, Studies, and Region .................................................................................... 32

Figure 3-13 Appended DataFrame with new columns ......................................................................... 33

Figure 3-14 Loading custom QIBs ......................................................................................................... 33

Figure 3-15 Schema of Album ............................................................................................................... 34

Figure 3-16 GET request of all albums .................................................................................................. 34

Figure 3-17 Nested Patient schema inside Study ................................................................................. 34

Figure 3-18 Table of API's endpoints .................................................................................................... 35

Figure 3-19 Converting list of QIBFeatures to Table ............................................................................. 35

Figure 3-20 Tree view of a table JSON .................................................................................................. 36

Figure 3-21 Converting QIBFeatures into scatterplot data ................................................................... 36

Figure 3-22 Sample result of scatterplot data returned ....................................................................... 37

Figure 3-23 Light/Dark mode of Grid, Plot and Database views respectively ...................................... 38

Figure 3-24 Sorting QIB by Albums/Date .............................................................................................. 38

Figure 3-25A QIB card menu ................................................................................................................. 38

Figure 3-26 Edit form ............................................................................................................................ 39

Figure 3-27 A loaded table .................................................................................................................... 39

Figure 3-28 Sorting arrow ..................................................................................................................... 39

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 8

Figure 3-29 Filtering for patient name .................................................................................................. 40

Figure 3-30 Pagination control at the bottom of table view ................................................................ 40

Figure 3-31 Edit, delete, add rows ........................................................................................................ 40

Figure 3-32 Column tagging form ......................................................................................................... 40

Figure 3-33 Toggling columns ............................................................................................................... 41

Figure 3-34 Toggling rows ..................................................................................................................... 41

Figure 3-35 Upload form ....................................................................................................................... 41

Figure 3-36 Valid new QIB file ............................................................................................................... 42

Figure 3-37 Valid custom QIB file .......................................................................................................... 42

Figure 3-38 Valid outcome list file ........................................................................................................ 42

Figure 3-39 Plot view ............................................................................................................................ 42

Figure 3-40 Generated scatterplot ....................................................................................................... 43

Figure 3-41 Album tab and List of selected album's studies ................................................................ 43

Figure 3-42 Patient tab ......................................................................................................................... 43

Figure 3-43 Patient edit form (Last name is noneditable) .................................................................... 44

Figure 3-44 Modality & region tab ........................................................................................................ 44

Figure 3-45 Modality CT's change into 'Computed tomography' is reflected in the table ................... 44

Figure 3-46 Feature & Feature Family tab ............................................................................................ 45

Figure 4-1 CRUD Availability Table ........................................................................................................ 47

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 9

ABBREVIATIONS

ACID - Atomicity, Consistency, Isolation, Durability

AGPL - Affero General Public License

API - Application programming interface

CRUD - Create, read, update and delete

CT - Computed tomography

DB - Database

DICOM - Digital Imaging and Communications in Medicine

GTV - Gross tumour volume

IOP - Input/output operations per second

JSON - JavaScript Object Notation

JSX - JavaScriptXML

PT - Short for PET, positron emission tomography

QIB - Quantitative Image Biomarkers

RDS - Relational Database Service

REST - Representational State Transfer

ROI - Region of Interest

RSNA - Radiological Society of North America

SPHN - Swiss Personalized Health Network

SQL - Structured Query Language

Bachelor Thesis

Web-based platform for managing quantitative image biomarkers 10

1. INTRODUCTION AND STATE OF THE ART

1.1 The field of radiomics

Advances in computing have led to changes in the field of medical imaging, particularly in cancer

care. Once largely a qualitative diagnostic tool (Sara Ranjbar, 2017, p. 223), that is, a tool to provide

on-hand information to aid in decision-making, a new branch of imaging research has emerged thanks to leaps in computational performance ,which has enabled the large-scale extraction and management of medical images. Radiomics, as it is called, is the field of medical research where high-throughput data is extracted from large numbers of imaging data that can come from multiple sources and patient profiles. The advantage of radiomics lies in number, whereby levying the sheer amount of data available (patients go through imaging multiple times during their treatment), researchers can glean quantitative imaging features from the images using computer image detection technologies. Radiomics finds its role in cancer treatment as a non-invasive enhancement, but not replacement, to more invasive traditional procedures during the process of diagnosis and assessment.

1.1.1 Biomarkers and features

Biomarkers are indicators of normal or abnormal biologic processes (Sara Ranjbar, 2017). An example of a well-known biomarker is high body temperature as indication of fever. In the context of cancer treatment, the main source of biomarkers come from biopsy samples. Features are a category of measurement in the process of gathering biomarker information. Continuing with the above example, body temperature in Celsius is a feature. Data from radiomics research not only can act as potential biomarkers, but due to its quantitativequotesdbs_dbs17.pdfusesText_23

[PDF] WEB-BASED PLATFORM FOR MANAGING IMAGE BIOMARKERS

Bachelor Thesis

Student : Nghi Tran

Professor : Adrien Depeursinge

WEB-BASED PLATFORM FOR

MANAGING IMAGE BIOMARKERS

August 2020

Bachelor Thesis

ABSTRACT

Bachelor Thesis

FOREWORD

Bachelor Thesis

TABLE OF CONTENTS

1. INTRODUCTION AND STATE OF THE ART .................................................................................... 10

1.1 The field of radiomics ................................................................................................................. 10

1.1.1 Biomarkers and features ...................................................................................................... 10

1.2 State of the art ........................................................................................................................... 10

1.2.1 General workflow of radiomics research ............................................................................. 10

1.2.2 Existing radiomics solutions ................................................................................................. 11

1.2.2.1 I2b2 ............................................................................................................................... 11

1.2.2.2 Radiomics Enabler ......................................................................................................... 13

1.2.3 Breaking down the workflow ............................................................................................... 13

1.2.4 Existing specialized products/libraries ................................................................................. 14

1.2.4.1 Kheops ........................................................................................................................... 14

1.2.4.2 Pyradiomics ................................................................................................................... 14

1.2.4.3 Scikit-learn .................................................................................................................... 15

1.3 Role and aim of this project ....................................................................................................... 15

2. METHODOLOGY ............................................................................................................................ 16

2.1 Designing the feature manager ................................................................................................. 16

2.1.1 Introduction to terminologies used ..................................................................................... 16

2.1.2 Use cases .............................................................................................................................. 16

2.1.3 Solution overview ................................................................................................................ 17

2.2 Technologies chosen .................................................................................................................. 18

2.2.1 Database .............................................................................................................................. 18

2.2.1.1 MySQL ........................................................................................................................... 18

2.2.2 Back-end + API ..................................................................................................................... 19

2.2.2.1 Flask .............................................................................................................................. 19

2.2.2.2 Pandas ........................................................................................................................... 19

2.2.2.3 SQLAlchemy .................................................................................................................. 19

2.2.3 Front-end ............................................................................................................................. 20

2.2.3.1 React ............................................................................................................................. 20

2.2.3 Architecture of project ......................................................................................................... 20

Bachelor Thesis

2.2.5 Technologies comparison .................................................................................................... 21

2.3 Tools used ................................................................................................................................... 21

2.3.1 Amazon Relational Database Service ................................................................................... 21

2.3.2 Local MySQL server .............................................................................................................. 23

2.3.3 DBeaver ................................................................................................................................ 23

2.3.4 Visual Studio Code ............................................................................................................... 24

2.3.5 GitHub .................................................................................................................................. 25

3. RESULTS ........................................................................................................................................ 26

3.1 Database ..................................................................................................................................... 26

3.1.1 Data model ........................................................................................................................... 26

3.1.2 Transforming a CSV file into database entities .................................................................... 27

3.1.2.1 CSV file input ................................................................................................................. 27

3.1.2.2 Steps of loading data into the database: ...................................................................... 28

3.1.3 Order of insertion................................................................................................................. 28

3.2 Back-end ..................................................................................................................................... 29

3.2.1 Defining the database schema with SQLAlchemy ............................................................... 29

3.2.2 ETL process ........................................................................................................................... 30

3.2.2.1 Loading raw feature sets ............................................................................................... 30

3.2.2.2 Loading custom QIB ...................................................................................................... 33

3.2.3 REST API endpoints .............................................................................................................. 34

3.2.3.1 Editing patient information (*) ..................................................................................... 35

3.2.3.2 Converting list of QIBFeatures into a table (**)............................................................ 35

3.2.3.3 Converting list of QIBFeatures into a scatterplot (***) ................................................ 36

3.3 Front-end .................................................................................................................................... 37

3.3.1 Dark mode ............................................................................................................................ 37

3.3.2 Grid View .............................................................................................................................. 38

3.3.2.1 Sorting QIBS .................................................................................................................. 38

3.3.2.2 Managing QIBs .............................................................................................................. 38

3.3.2.3 QIB Table view .............................................................................................................. 39

Bachelor Thesis

3.3.2.4 Uploading QIBs .............................................................................................................. 41

3.3.3 Plot View .............................................................................................................................. 42

3.3.3.1 Statistics ........................................................................................................................ 42

3.3.3.2 Generating a bivariate scatterplot ................................................................................ 42

3.3.4 Database View ..................................................................................................................... 43

3.3.4.1 Album ............................................................................................................................ 43

3.3.4.2 Patient ........................................................................................................................... 43