54 citations · 100 across the 5 of their papers we have counts for
5 papers
Bag of Visual Words (BoVW) with Deep Features -- Patch Classification Model for Limited Dataset of Breast Tumours
Suvidha Tripathi, Satish Kumar Singh, Lee Hwee Kuan
Currently, the computational complexity limits the training of high resolution gigapixel images using Convolutional Neural Networks. Therefore, such images are divided into patches…
Ensembling Handcrafted Features with Deep Features: An Analytical Study for Classification of Routine Colon Cancer Histopathological Nuclei Images
Suvidha Tripathi, Satish Kumar Singh
The use of Deep Learning (DL) based methods in medical histopathology images have been one of the most sought after solutions to classify, segment, and detect diseased biopsy sampl…
An Object Aware Hybrid U-Net for Breast Tumour Annotation
Suvidha Tripathi, Satish Kumar Singh
In the clinical settings, during digital examination of histopathological slides, the pathologist annotate the slides by marking the rough boundary around the suspected tumour regi…
Cell nuclei classification in histopathological images using hybrid OLConvNet
Suvidha Tripathi, Satish Kumar Singh
Computer-aided histopathological image analysis for cancer detection is a major research challenge in the medical domain. Automatic detection and classification of nuclei for cance…
An End-to-End Breast Tumour Classification Model Using Context-Based Patch Modelling- A BiLSTM Approach for Image Classification
Suvidha Tripathi, Satish Kumar Singh, Hwee Kuan Lee
Researchers working on computational analysis of Whole Slide Images (WSIs) in histopathology have primarily resorted to patch-based modelling due to large resolution of each WSI. T…