collaborators

6 papers

cs.CV2026

Occlusion-Aware Panoptic Segmentation with Joint Position Embedding and Occlusion-Level Attention

Wenbo Wei, Jun Wang, Shan Raza +1

Panoptic segmentation in complex scenes remains challenging because of occlusions, yet modern approaches often neglect occlusion modelling. In this paper, we propose Position Embed…

q-bio.TO2026

A deep learning framework for glomeruli segmentation with boundary attention

Behnaz Elhaminia, Catherine King, Jiaqi Lv +5

Accurate detection and segmentation of glomeruli in kidney tissue are essential for diagnostic applications. Traditional deep learning methods primarily rely on semantic segmentati…

cs.LG2025

ModalSurv: Investigating opportunities and limitations of multimodal deep survival learning in prostate and bladder cancer

Noorul Wahab, Ethar Alzaid, Jiaqi Lv +3

Accurate survival prediction is essential for personalised cancer treatment. We propose ModalSurv, a multimodal deep survival framework integrating clinical, MRI, histopathology, a…

eess.IV2025

Leveraging Pathology Foundation Models for Panoptic Segmentation of Melanoma in H&E Images

Jiaqi Lv, Yijie Zhu, Carmen Guadalupe Colin Tenorio +3

Melanoma is an aggressive form of skin cancer with rapid progression and high metastatic potential. Accurate characterisation of tissue morphology in melanoma is crucial for progno…

eess.IV2025

From Traditional to Deep Learning Approaches in Whole Slide Image Registration: A Methodological Review

Behnaz Elhaminia, Abdullah Alsalemi, Esha Nasir +6

Whole slide image (WSI) registration is an essential task for analysing the tumour microenvironment (TME) in histopathology. It involves the alignment of spatial information betwee…

eess.IV2025

Deep Learning Based Segmentation of Blood Vessels from H&E Stained Oesophageal Adenocarcinoma Whole-Slide Images

Jiaqi Lv, Stefan S Antonowicz, Shan E Ahmed Raza

Blood vessels (BVs) play a critical role in the Tumor Micro-Environment (TME), potentially influencing cancer progression and treatment response. However, manually quantifying BVs…