On The Move Ultrasound Diagnosis on Mobile

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Humayun Irshad 1 , Sajjad Athar 1 , Faisal Shahzad 1,2 , Adnan Bashir 1,2 , Dr. Farhat Jehan 3 1 Next Generation Intelligent Networks Research Center (nexGIN RC), 2 National University of Computer and Emerging Sciences (FAST-NUCES), Islamabad 3 Telemedinice and e-Health Training, Holy Family Hospital Rawalpindi http://rpms.nexginrc.org/ http://www.nexginrc.org/ On The Move Ultrasound Diagnosis on Mobile

Transcript of On The Move Ultrasound Diagnosis on Mobile

Humayun Irshad1, Sajjad Athar1, Faisal Shahzad1,2, Adnan Bashir1,2, Dr. Farhat Jehan3

1Next Generation Intelligent Networks Research Center (nexGIN RC), 2National University of Computer and Emerging Sciences (FAST-NUCES), Islamabad

3Telemedinice and e-Health Training, Holy Family Hospital Rawalpindi

http://rpms.nexginrc.org/ http://www.nexginrc.org/

On The Move Ultrasound Diagnosis on Mobile

Agenda

1 • Background

2 •Objectives

3 •Methods

4 • Comparative Studies

5 • Image Processing

6 • Future Goals

7 •Questions

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Background

• Health care situation in Pakistan is below the international standards due to scarcity and unavailability of specialists

• Lack of Health Infrastructure • Shortage of trained Radiologists • Few Radiologists specially in remote areas • Poor antenatal facilities in remote areas

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1. Increase the number of radiologists and send the radiologists to remote areas

2. Use of Information and Communication Technology (ICT) to improve efficiency of existing health care facilities

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Solutions

Health Care Professionals

Patients

Tools

Connectivity

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Idea

Development of system to extend the services of radiologist to remote

areas

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System Architecture

• Developed a web interface to upload ultrasound images and patient medical data

• Developed a web server and EMR for data storage and interaction with Mobile applications and CDSS

• Developed an application for radiologists to diagnosis ultrasound on mobile

• Implemented image processing techniques for image content enhancement, noise removal and transmission

• Implemented the algorithms for image zooming • SMS based notification and alerts for radiologists

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System Features & Methodology

Ultrasound Machine

Patient

Web Site GPRS Server

EMR

CDSS GSM Doctor

System Flow

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Website

• Equipment – InnovaSound Ultrasound System: Direct Medical

Systems – 3.5 MHz Probe connected to Laptop

Methodology

• Enable Doctors to view Patient History

• Enable Doctors to views Ultrasound Images

• Give Feedback back to server

• Server send SMS to doctor and patient about any update

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Mobile Application

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Mobile Application

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Mobile Application

In hospital evaluation of the system before incorporating into routine practice.

Research Study

• Collected data of 60 patients from the Holy Family Hospital

• Each record contains specific ultrasound images

• Two way to diagnose: – Laptop

– Mobile

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Research Study

• Mean Age 42 (SD 13)

• Male 11 • Female 49

Results

•Hepatobiliary –Cholelithiais 16 –Chronic Liver Disease 6 –Liver Abscess 2

•Urinary – Nephrolithiasis/ Hydronephrosis 4 – Bladder Calculi 2 – Hypertrophy of Prostate 7

Surgical Conditions

•Gynecological – Fibroids 8 – Adnexal mass 6

•Obstetrics –Antenatal Scan 9

Gynae/Obst Conditions

Frequency

Percent

Valid Percent

Cumulative Percent

Laptop Ultrasound Diagnosis same as Mobile Telesonography

45

75.0

75.0

75.0

Laptop Ultrasound Diagnosis part of differentials of Mobile Telesonography

6

10.0

10.0

85.0

Both Diagnosis Different

9

15.0

15.0

100.0

Results

• Same diagnosis

– 51 cases – Sensitivity :85 %

Comparison of Diagnosis

Level of Certainty % age

very certain

88 %

somewhat certain

7 %

uncertain

5 %

Certainty Level in Correct diagnosis

• Satisfaction of Distant Radiologist on Mobile Application – 48 patients

– Image relevance & quality of the study

Satisfaction Level

0

10

20

30

40

50

60

70

Image Size 10

KB

Image Size 20

KB

Image Size 30

KB

Image Size 40

KB

Image Size 50

KB

Image Size 100

KB

Average Image Access Time (Seconds)

Average Image Access Time (Seconds)

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Performance Analysis

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Website

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Website

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Website

Image Segmentation • Partitioning of digital image in segments • To simplify an image into something that is more

meaningful and easier to analyze Feature Extraction • Extract important and relevant features for decision

making Classification • Classify images by observing the features and other

relevant data from the EMR and Grand Chart

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Future Work & Image Processing

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Original Background Image Noise Removed

Enhancement Thresholding

Current Working

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1-ROI and Partitioning

2-Fuzzy Mean Clustering

Current Working

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3-Salient Edge Map

4-Contour Extraction and BDP

Current Working

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5-Deforming Snake

6-Deforming Snake

Current Working

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Grand Chart (Femur Length Growth)

Ultrasound Diagnosis on PDA

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Grand Chart

Thank you

Questions?

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