Automatic seed point selection in ultrasound echography images of - - PowerPoint PPT Presentation

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Automatic seed point selection in ultrasound echography images of - - PowerPoint PPT Presentation

May 13, 2023 132 likes •553 views

Automatic seed point selection in ultrasound echography images of breast using texture features CSS400 Project Management Progress presentation Sirindhorn International Institute of Technology 2015 Project Member Name : Mr.Apichon

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Automatic seed point selection in ultrasound echography images of breast using texture features

CSS400 Project Management Progress presentation Sirindhorn International Institute of Technology 2015

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Project Member

Name : Mr.Apichon Kitvimonrat Major : Computer Science Name : Mr.Krisada Vivek Major : Computer Science

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Advisor

Dr

  • Dr. Stanis

islav S. . Mak akhanov (P (Professor)

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What is this project about?

  • Image processing technique (Algorithm) that can differentiate between tumor area

(Bad) and normal tissue (good)from the ultrasound image.

  • It will identify which state of cancer you are in.
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Problem in tumor diagnosis operation

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Motivation / Passion

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Motivation / Passion

http://www.healthline.com/health/breast-cancer/survival-facts-statistics

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  • According to The National

Institutes of Health (NIH) statistic breast cancer is the top leading cause of death in the US/World with around 584,881 deaths each year.

  • In 2015, around 40,290 of woman

dead from the breast cancer late detection.

Motivation / Passion

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  • Early detection of potential

tumors can decrease change of death

  • To do that we need to make

the image processing better.

http://breast-cancer.ca/wp-content/uploads/2014/11/Figure-8-2-Survival-According-to-Stage.jpg

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Algorithm

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Select input picture

  • utput picture

Image Analysis

Overview of tumor analytic

Scan and stored in database

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How to analysis ultrasound image

Any size * Any size 200 pixel * 200 pixel 10 pixel * 10 pixel Highest potential window that can be the tumor

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plot seed point

Draw contour around the area

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User-Interface/User Experience (Mock up flow)

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C#/C++ C programming family Certified Microsoft Internship/Partner

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Cure Tumor

Username Password

Login

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Cure Tumor

KDV Password

Login

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Cure Tumor

Username ********

Login

KDV

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Cure Tumor

KDV Password

Login

********

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Cure Tumor

KDV Password

Login

********

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Cure Tumor

name name name name

Log out Exit File

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Cure Tumor

name name name name

Log out Exit File

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Cure Tumor

name name name name

Log out Exit File

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Cure Tumor

Name: Birthdate: Age: Previous Scan: name name name name

Log out Exit File

Notes: Note here. Note here. Note here. Note here. Note here. Note here. Note here. Note here. Note here. Note here. Note here.

Select

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Cure Tumor

Name: Birthdate: Age: Previous Scan: name name name name

Log out Exit File

Notes: Note here. Note here. Note here. Note here. Note here. Note here. Note here. Note here. Note here. Note here. Note here.

Select

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Cure Tumor Log out Exit File

Analyst Select Image Cancel

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Cure Tumor Log out Exit File

Analyst Select Image Cancel

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Cure Tumor Loading…

Processing Requested…

Log out Exit File

Cancel

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Cure Tumor Loading…

Analysing…

Log out Exit File

Cancel

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Cure Tumor Export… Page Setup… Exit File Diagnose complete

The result replace here. The result replace here. The result replace here. The result replace here.

View more

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Cure Tumor Export… Page Setup… Exit File Diagnose complete

The result replace here. The result replace here. The result replace here. The result replace here.

View more

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Cure Tumor Export… Page Setup… Exit File Diagnose complete

The result replace here. The result replace here. The result replace here. The result replace here.

Back to main

Original Analysed Note replace here. Note replace here. Note replace here. Note replace here.

Print

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Cure Tumor Export… Page Setup… Exit File Diagnose complete

The result replace here. The result replace here. The result replace here. The result replace here.

Back to main

Original Analysed Note replace here. Note replace here. Note replace here. Note replace here.

Print

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Cure Tumor

name name name name

Log out Exit File

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Demo Time

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Database

Hospital’s DB We are here

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DB 0% Algorithm 25% UI/UX 90%

Project process

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Problem in process

  • Learning curve
  • Software Engineer not familiar with Image processing
  • Multimedia Processing (CSS424)
  • Pattern Recognition & Machine Learning
  • Parallel and Distribute computing
  • (Programming)
  • Image
  • Size
  • Quality
  • Source
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Challenges

  • Result accuracy must be greater than 80 %
  • Diagnosis operation should be within 5 minute or not more than that
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Future

  • Current -> Internal Computation
  • Large Image take time to convert
  • Future -> Cloud/Server Computation
  • Parallel Computing (CUDA)(GPU/CPU)
  • Machine Learning
  • Classification
  • Reason ->
  • More computational power
  • Support multiple platform (Dr.Boontawee’s request)