1 citations · 3 across the 6 of their papers we have counts for
6 papers
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…
KongNet: A Multi-headed Deep Learning Model for Detection and Classification of Nuclei in Histopathology Images
Jiaqi Lv, Esha Sadia Nasir, Kesi Xu +4
Accurate detection and classification of nuclei in histopathology images are critical for diagnostic and research applications. We present KongNet, a multi-headed deep learning arc…
MitoDetect++: A Domain-Robust Pipeline for Mitosis Detection and Atypical Subtyping
Esha Sadia Nasir, Jiaqi Lv, Mostafa Jahanifar +1
Automated detection and classification of mitotic figures especially distinguishing atypical from normal remain critical challenges in computational pathology. We present MitoDetec…
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…
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…
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…