Expansion Pathology Framework for classification of Early Stage Neoplastic Breast Lesions (Normal, UDH, ADH and DCIS) - Matlab
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
Classification
Seg_Evaluation
Seg_FeatureExt
LICENSE
README.md

README.md

ExPath

ExPath Image Classification Framework

Expansion Pathology Iamge Classification: This framework classify Expansion pathology images into Normal, Benign Breast Lesions (UDH and ADH) and Pre-invasvie Breast Leasions. This framework consisted of three components:

1- Nuclei Segmentation and Feature Extraction written in matlab

2- Nuclei Segmentation Evalaution written in matlab using LabelMe API

3- Image Classification written in R

This image classification framework for post-expansion DAPI-stained images includes foreground detection, nucleus seed detection, and nuclear segmentation. Following application of the framework, we extract three kinds of features from each segmented nucleus from both the pre-expanded and post-expanded images: nuclear morphology features, nuclear intensity features, and nuclear texture features.