output
20172019
most citedMILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images

345 citations

5 papers

cs.CV2019★ 86 cited

Learning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring

Talha Qaiser, Nasir M. Rajpoot

Estimating over-amplification of human epidermal growth factor receptor 2 (HER2) on invasive breast cancer (BC) is regarded as a significant predictive and prognostic marker. We pr…

cs.CV2018★ 345 cited

MILD-Net: Minimal Information Loss Dilated Network for Gland Instance Segmentation in Colon Histology Images

Simon Graham, Hao Chen, Jevgenij Gamper +5

The analysis of glandular morphology within colon histopathology images is an important step in determining the grade of colon cancer. Despite the importance of this task, manual s…

cs.CV2018★ 277 cited

Micro-Net: A unified model for segmentation of various objects in microscopy images

Shan E Ahmed Raza, Linda Cheung, Muhammad Shaban +5

Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images. We present a convolution neural network (CNN) based…

stat.ML2018★ 1 cited

Pseudo-marginal Bayesian inference for supervised Gaussian process latent variable models

Charles Gadd, Sara Wade, Akeel Shah +1

We introduce a Bayesian framework for inference with a supervised version of the Gaussian process latent variable model. The framework overcomes the high correlations between laten…

cs.CV2017★ 162 cited

Her2 Challenge Contest: A Detailed Assessment of Automated Her2 Scoring Algorithms in Whole Slide Images of Breast Cancer Tissues

Talha Qaiser, Abhik Mukherjee, Chaitanya Reddy Pb +19

Evaluating expression of the Human epidermal growth factor receptor 2 (Her2) by visual examination of immunohistochemistry (IHC) on invasive breast cancer (BCa) is a key part of th…