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adaptive-landmark-based-spectral-clustering-alsc-

This algorithm is referred to as the ALSC algorithm. The proposed algorithm comprises three phases and uses parallel processing to speed up its performance. The main advantages of the proposed algorithm are determining the optimal number of clusters and producing high clustering accuracy with the identification of the number of clusters.

another-digital-pathology

at_costofresistance_lvmodel

This repository contains the code to generate the figures in our research paper: Strobl et al (2020), Turnover modulates the need for a cost of resistance in adaptive therapy published in Cancer Research.

athena

Computational Framework to Analyse Spatial Heterogeneity in Visum, IMC or MIBI data sets

automatic-detection-and-uncertainty-quantification-of-landmarks-on-elastic-curves

Automatic Detection and Uncertainty Quantification of Landmarks on Elastic Curves, by Justin Strait, Oksana Chkrebtii, Sebastian Kurtek

basic_digital_pathology

blca_lnprediction

repository of code used for Harmon, Sanford et al "Multi-resolution Application of Artificial Intelligence in Digital Pathology for Prediction of Positive Lymph Nodes from Primary Tumors in Bladder Cancer"

breast-cancer-machine-learning-model

A Machine Learning Model That Classifies Images of Breast Cell Nuclei as Benign or Malignant

cam-4m17

comparebigwarptransformations

Allows for qualitative and quantitative analysis of image transformations generated using FIJI BigWarp

cse-573-project_1-color_channel_alignment_and_image_warping

A project on Color Channel Alignment and Image Warping done using MATLAB

cusa

Code for analysis performed in Cadwell et al., 2020 (CUSA Digital Pathology Validation Study)

cytological-image-thresholding

Minimal impl of the paper `Adaptive Local Thresholding for Detection of Nuclei in Diversely Stained Cytology Images`

deep-learning-image-compression-

Image Compression Deep Learning Based on Digital Whole Slide Pathology Images

detection-of-olive-tree-diseases

The identification of plant diseases especially of the olive tree remains very important. the integration of artificial intelligence can play a very important role in setting up a model for classifying images of different phytosanitary problems

diffusion_digital_pathology

this is the code repository related to the paper "Generating synthetic data in digital pathology through diffusion models: a multifaceted approach to evaluation"

digipathoimageanalysis

List of academic institutes/companies working on computer-based digital pathology image analysis

digipathtools

digital-pathology

End-to-end analysis tool for whole-slide images following Traumatic Brain Injury (Capstone I)

digital-pathology-old

outdated version

digital-pathology-tutorial

Federated digital pathology: classification of Acute Myeloid Leukemia (AML) cells with a CNN.

digital_pathology_deeplearningvsclassicalfeatures_python_matlab

This work is part of the course CS904 (Computational Biology, Warwick University). We classify tissues slides into eight different classes with a deep learning approach and compare the results to classification with a SVM that was trained on handcrafted features.

digital_pathology_neuroinflammation

digital_pathology_wirtzlab

digitalpathology

This is a repo to share to public community Digital Pathology (DP) web application

eedap

Evaluation Environment for Digital and Analog Pathology

fast-feature-matching-with-linear-transformers

Fast and memory efficient transformers based feature matching model.

fast_wsi_color_norm

Codes for Fast GPU-Enabled Color Normalization of Whole Slide Images in Digital Pathology

fluorescent_nuclei_segregation

This is an implementation of nuclei segmentation method for segregating clumped nuclei in DAPI in Fluorescence images.

fqpath

No-Reference Focus Quality Assessment of Digital Pathology Images [IEEE TMI 2019]