activity
20172021
most citedLearning Where to See: A Novel Attention Model for Automated Immunohistochemical Scoring

86 citations · 89 across the 3 of their papers we have counts for

collaborators

8 papers

eess.IV20213 cited

Classification of COVID-19 via Homology of CT-SCAN

Sohail Iqbal, H. Fareed Ahmed, Talha Qaiser +2

In this worldwide spread of SARS-CoV-2 (COVID-19) infection, it is of utmost importance to detect the disease at an early stage especially in the hot spots of this epidemic. There…

cs.CV2020

HydraMix-Net: A Deep Multi-task Semi-supervised Learning Approach for Cell Detection and Classification

R. M. Saad Bashir, Talha Qaiser, Shan E Ahmed Raza +1

Semi-supervised techniques have removed the barriers of large scale labelled set by exploiting unlabelled data to improve the performance of a model. In this paper, we propose a se…

cs.CV201986 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

Methods for Segmentation and Classification of Digital Microscopy Tissue Images

Quoc Dang Vu, Simon Graham, Minh Nguyen Nhat To +11

High-resolution microscopy images of tissue specimens provide detailed information about the morphology of normal and diseased tissue. Image analysis of tissue morphology can help…

cs.CV2018

Leveraging Unlabeled Whole-Slide-Images for Mitosis Detection

Saad Ullah Akram, Talha Qaiser, Simon Graham +3

Mitosis count is an important biomarker for prognosis of various cancers. At present, pathologists typically perform manual counting on a few selected regions of interest in breast…

cs.CV2018

Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge

Mitko Veta, Yujing J. Heng, Nikolas Stathonikos +30

Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is highly subjective an…