index.qmd

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title: "Fall 2024 STAT390 (CMIL Classification)" 
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**Aim: The objective of this project is to identify the severity of potential eye cancer by looking at a particular eye tissue of the patient.**

In medical terms, we want to develop a machine learning model to accurately classify *Conjunctival melanocytic intraepithelial lesions **(C-MIL)*** as per the *WHO 2022 classification system*. Providing a reproducible and accurate grading of C-MIL will help doctors select the most appropriate management plan for the patient.

The Northwestern University STAT390 Class of Fall 2024 has made the following progress on this project:

![](images/HomeImage.png){fig-align="center"}

**Step 1:**  Extracting tissue slices from Whole Slice Images (**WSI**) using QuPath

**Step 2:**  Matching similar tissue slices across the different stains (**H&E, Melan-A, Sox-10**) for each patient when there is a correct match 

**Step 3:**  Detecting and extracting the epithelium and stroma for each tissue slice. Send to pathologist team

- *Pathologist Team will annotate H&E slice with high grade, low grade, and benign regions and send back to us*

**Step 4:**  Orienting matched slices and apply patching across epithelium for matched slices

**Literature Review**: Researched adaptive pooling, cross view transformer, advantages of square patches, padding effect, etc.