School of Computer ScienceQueen’s UniversityBelfast

Assignment: Prostate Cancer Diagnosis

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

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)

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

School of Computer ScienceQueen’s UniversityBelfast

BPH

• Large white glandular areas

• Lots of white pixels

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

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

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

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.

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

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

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

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

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

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

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.

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.

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.

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.

School of Computer ScienceQueen’s UniversityBelfast

Report• Introduction• Preprocessing• Binarisation• Postprocessing• Feature Extracture• Classification and Testing• Conclusion• Appendix

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

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

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!

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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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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Appendix

• Include only the code you have written.

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.

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