TIA Centre: Software
- : Self-supervision for Classification of Pathology Images with Limited Annotations ()
- : Interactive segmentation of nuclei in histology images ()
- : SOTA algorithm for simultaneous segmentation and classification of nuclei in H&E images ()
- : Multiple Instance Learning of Amyloid Proteins (Minhas)
- : A machine learning predictor for antimicrobial activity (Minhas)
- : LUPI-SVM based classification of protein complexes using binding affinity (Minhas)
- : Predicts Liver Cirrhosis from ultrasound images (Minhas)
- : Host-Pathogen Protein Interaction Prediction (Minhas)
- : Calmodulin (CaM) intEraction Learning System (Minhas)
- : Context Aware Feature Mapping for mining high dimensional biomedical data (Minhas)
- SC-CNN: Deep learning code for cell detection and phenotyping in H&E images (Feb 2017) [ code for our TMI May 2016 paper; available on request by email to Nasir Rajpoot; Labelled cell nuclei data ]
- Cell Words for modelling the appearance of cells in histopathology images (March 2015)
- Stain normalization toolbox for histopathology images (Feb 2015)
- THeCoT: Spatial Model of Tumour Heterogeneity in Colorectal Adenocarcinoma (BMC Bioinformatics, 2015)
- : Cell localised protein network analysis (Bioinformatics, 2014)
- GBHC: Bayesian Hierarchical Clustering with a Gaussian Conjugate Prior for clustering of Gene Expression profiling data (PLoS ONE, 2014)
- Cell/Nuclei Detection using LIPSyM for H&E and H&DAB histopathology images (J Path Informatics, 2012)