School of Computer Science Queen’s University Belfast Assignment: Prostate Cancer Diagnosis.
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Transcript of School of Computer Science Queen’s University Belfast Assignment: Prostate Cancer Diagnosis.
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School of Computer ScienceQueen’s UniversityBelfast
Assignment: Prostate Cancer Diagnosis
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School of Computer ScienceQueen’s UniversityBelfast
Prostate Cancer Diagnosis
• 32,000 men die every year.
• Methods of diagnosis – Prostate specific antigen (PSA) blood test. – Needle biopsy.
• Tissue sample mounted on a slide
• Analysed under microscope by a pathologist
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School of Computer ScienceQueen’s UniversityBelfast
Biopsy Analysis
• Pathologist classifies each slide into three classes indicating the following conditions:– normal muscular tissue, Stroma (St)
– intermediate stage, Benign Prostatic Hyperplasia (BPH)
– abnormal tissue development , Cancer (Ca)
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School of Computer ScienceQueen’s UniversityBelfast
Stroma
• Grey nuclei in a lighter grey tissue background
• No black pixels or white pixels
• No large scale structures
• Texture like
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School of Computer ScienceQueen’s UniversityBelfast
BPH
• Large white glandular areas
• Lots of white pixels
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School of Computer ScienceQueen’s UniversityBelfast
Biopsy Analysis
• Very dark nuclei congregate in prominent clusters
• Lots of dark or black pixels
• White glandular area is much small
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School of Computer ScienceQueen’s UniversityBelfast
Training Images
• Training images 1, 2 and 3 are for BPH class• Training images 4, 5 and 6 are for Cancer class • Training images 7, 8 and 9 are for Stroma class
• Images are in directory S:\Library\Level3\CSC312\VisionSystem
• assign_04_1.jpg …. assign_04_9.jpg• Copy to your Usernumber directory
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School of Computer ScienceQueen’s UniversityBelfast
Aim
• Use nine training images to design an automatic image classification system that will diagnose biopsy tissue sample images correctly
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School of Computer ScienceQueen’s UniversityBelfast
Learning Outcomes
4. Be able to describe the underlying mathematical framework and explain the concepts of these operations.
5. Be able to develop an automated image processing system.
6. Be proficient in VisionSystem.7. Be able to write an image processing
report.
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School of Computer ScienceQueen’s UniversityBelfast
Level 3 Learning Outcomes
• Less emphasis on knowledge and more on critical thinking skills
5. Be able to develop an automated image processing system.
– Apply– Analysis– Evaluation– Synthesis
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School of Computer ScienceQueen’s UniversityBelfast
Generic automated system
Image Acquisition
Image Data
Pre-processing
Image Data
Segmentation
Image Data
FeatureExtraction
Feature Descriptions
Classificationand/or
interpretationInformation
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School of Computer ScienceQueen’s UniversityBelfast
At each stage….
• Experiment with applying the different techniques at your disposal
• Analyse the results and evaluate them
• Select the technique that gives the best result
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School of Computer ScienceQueen’s UniversityBelfast
Preprocessing• No communication noise removal required.• Linear stretching
– Same values of I1 and I2 must be used fro all training images
– Or, write method that automatically calculates optimal I1 and I2 for each image
• Same value of gamma must be used for power law• You cannot evaluate the preprocessing until you
have performed thresholding during segmentation
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School of Computer ScienceQueen’s UniversityBelfast
Discussion Forum
• Will answer questions for each stage only the week after the lecture
• Promote continual working at the assignment
• Next week will answer questions related to preprocessing and binarisation stage of brightness based segmentation
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School of Computer ScienceQueen’s UniversityBelfast
Segmentation• Segmentation threshold:
– Analyse histograms of preprocessed training images
– From analysis select best threshold overall, but must use this same value for all training images
– Or use automatic technique
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School of Computer ScienceQueen’s UniversityBelfast
Deadline
• 3:00pm Mon 3rd May
• Hand in at general office SARC
• Sign your name on list
• Must be witnessed by one of the secretarial staff
• Plan appropriately, set target date 2-3 days before deadline.
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School of Computer ScienceQueen’s UniversityBelfast
Deadline
• Assessed work submitted after the deadline will be penalised at the rate of 5% of the 40 marks available for each working day late up to a maximum of five working days, after which a mark of zero shall be awarded.
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School of Computer ScienceQueen’s UniversityBelfast
Exemptions• Exemptions shall be granted only if there
are extenuating circumstances, and where the student has made a case in writing to the member(s) of staff designated by the School within three days of the deadline for submission.
• Send me a completed Application for Exemption for Penalty form with supporting documentation, – e.g., doctor’s note specifying days you were unable to
work.– copy of what you have done so far.
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School of Computer ScienceQueen’s UniversityBelfast
Exemptions
• As soon as you know you will need an exemption inform me. Do not wait until after you are better, etc, and then ask.
• No applications for exemption will be given on the week before the deadline without a draft report showing the preprocessing, segmentation and feature extraction have been completed.
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School of Computer ScienceQueen’s UniversityBelfast
Report• Introduction• Preprocessing• Binarisation• Postprocessing• Feature Extracture• Classification and Testing• Conclusion• Appendix
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School of Computer ScienceQueen’s UniversityBelfast
Each Section
• Explain how you applied the various techniques to this particular problem
• Present results– Images, tables and graphs
• Describe your analysis of the results.• Evaluate the different techniques.• The more techniques you experiment with
the greater the marks
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School of Computer ScienceQueen’s UniversityBelfast
Example - Classification
• Describe how you applied linear discriminant to this particular case
• Analyse results
• Describe how you applied nearest-neighbour to this particular case
• Analyse results
• Compare and evaluate
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School of Computer ScienceQueen’s UniversityBelfast
Presenting Results
• Image, table or graphics• Concise as possible• Nine training images means you cannot present all
training image results at all stages • Only present images you really need to make your
point• Do not make a point and present no supporting
evidence!
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School of Computer ScienceQueen’s UniversityBelfast
Inserting Images
• Run VisionSystem to display what images you want
• Press PrtSc key to capture a screenshot• Open Microsoft PhotoEditor• Select Paste as New Image under Edit• Press select button on Toolbar• Cut portion of image you want• Paste into Word document
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School of Computer ScienceQueen’s UniversityBelfast
Style
• Number different sections and pages• Label figures, and give each figure a caption
describing what it is:– Figure 1: Binary training image with a threshold of x.
• Must refer to figures in your text.• Number equations• No pseudo-code in main document!• Maximum of ten pages (not including appendix)
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School of Computer ScienceQueen’s UniversityBelfast
Appendix
• Include only the code you have written.
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School of Computer ScienceQueen’s UniversityBelfast
Assessment
• Understanding of how techniques work.• Evidence of your ability to apply them
appropriately.• Your ability to analyse and evaluate the
results.• Effectiveness of your final solution.• Your proficiency with VisionSystem• Quality of report.
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School of Computer ScienceQueen’s UniversityBelfast
Test Images
• Five test images
• Images will be in directory S:\Level3\Csc312\ VisionSystem on your return from the Easter break.
• assign_04_10.jpg …. assign_04_14.jpg
• Copy to your Usernumber directory