On The Move Ultrasound Diagnosis on Mobile
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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
10/14/2013 Ultrasound Diagnosis on Mobile 4
Solutions
Health Care Professionals
Patients
Tools
Connectivity
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Idea
• 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
10/14/2013 9 Ultrasound Diagnosis on Mobile
• 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
• 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
•Hepatobiliary –Cholelithiais 16 –Chronic Liver Disease 6 –Liver Abscess 2
•Urinary – Nephrolithiasis/ Hydronephrosis 4 – Bladder Calculi 2 – Hypertrophy of Prostate 7
Surgical 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
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
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