School of Computer Science Queen’s University Belfast Assignment: Prostate Cancer Diagnosis

School of Computer Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast Stroma Grey nuclei in a lighter grey tissue background No black pixels or white pixels No large scale structures Texture like

School of Computer Science Queen’s University Belfast BPH Large white glandular areas Lots of white pixels

School of Computer Science Queen’s University Belfast Biopsy Analysis Very dark nuclei congregate in prominent clusters Lots of dark or black pixels White glandular area is much small

School of Computer Science Queen’s University Belfast 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 Science Queen’s University Belfast Aim Use nine training images to design an automatic image classification system that will diagnose biopsy tissue sample images correctly

School of Computer Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast Generic automated system Image Acquisition Image Data Pre- processing Image Data Segmentation Image Data Feature Extraction Feature Descriptions Classification and/or interpretation Information

School of Computer Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast Deadline 3:00pm Mon 3 rd 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast Report Introduction Preprocessing Binarisation Postprocessing Feature Extracture Classification and Testing Conclusion Appendix

School of Computer Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast 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 Science Queen’s University Belfast 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

School of Computer Science Queen’s University Belfast 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)

School of Computer Science Queen’s University Belfast Appendix Include only the code you have written.

School of Computer Science Queen’s University Belfast 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 Science Queen’s University Belfast 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