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
Data
Image
Acquisition
Image
Data
Preprocessing
Segmentation
Feature
Descriptions
Information
Classification
and/or
interpretation
School of Computer Science
Queen’s University
Belfast
Image
Data
Feature
Extraction
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 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 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
School of Computer Science
Queen’s University
Belfast