:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Dewbury, Jarett, Tai, Chi-en Amy, Wong, Alexander
Format:	Preprint
Published:	2025
Subjects:	Image and Video Processing Computer Vision and Pattern Recognition
Online Access:	https://arxiv.org/abs/2501.09185
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Cancer-Net PCa-MultiSeg: Multimodal Enhancement of Prostate Cancer Lesion Segmentation Using Synthetic Correlated Diffusion Imaging
by: Dewbury, Jarett, et al.
Published: (2025)

Optimizing Synthetic Correlated Diffusion Imaging for Breast Cancer Tumour Delineation
by: Tai, Chi-en Amy, et al.
Published: (2024)

Improving Breast Cancer Grade Prediction with Multiparametric MRI Created Using Optimized Synthetic Correlated Diffusion Imaging
by: Tai, Chi-en Amy, et al.
Published: (2024)

Using Multiparametric MRI with Optimized Synthetic Correlated Diffusion Imaging to Enhance Breast Cancer Pathologic Complete Response Prediction
by: Tai, Chi-en Amy, et al.
Published: (2024)

Enhancing Clinically Significant Prostate Cancer Prediction in T2-weighted Images through Transfer Learning from Breast Cancer
by: Tai, Chi-en Amy, et al.
Published: (2024)

Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images
by: Tai, Chi-en Amy, et al.
Published: (2023)

PCa-RadHop: A Transparent and Lightweight Feed-forward Method for Clinically Significant Prostate Cancer Segmentation
by: Magoulianitis, Vasileios, et al.
Published: (2024)

MicroSegNet: A Deep Learning Approach for Prostate Segmentation on Micro-Ultrasound Images
by: Jiang, Hongxu, et al.
Published: (2023)

Optimizing Federated Learning Configurations for MRI Prostate Segmentation and Cancer Detection: A Simulation Study
by: Moradi, Ashkan, et al.
Published: (2025)

Using Diffusion Models to Generate Synthetic Labelled Data for Medical Image Segmentation
by: Saragih, Daniel, et al.
Published: (2023)

Registration-Enhanced Segmentation Method for Prostate Cancer in Ultrasound Images
by: Sang, Shengtian, et al.
Published: (2025)

Phi-SegNet: Phase-Integrated Supervision for Medical Image Segmentation
by: Ali, Shams Nafisa, et al.
Published: (2026)

SegX: Improving Interpretability of Clinical Image Diagnosis with Segmentation-based Enhancement
by: Zhang, Yuhao, et al.
Published: (2025)

Classification of Gleason Grading in Prostate Cancer Histopathology Images Using Deep Learning Techniques: YOLO, Vision Transformers, and Vision Mamba
by: Malekmohammadi, Amin, et al.
Published: (2024)

Gland Segmentation Using SAM With Cancer Grade as a Prompt
by: Zhu, Yijie, et al.
Published: (2025)

T2-Only Prostate Cancer Prediction by Meta-Learning from Bi-Parametric MR Imaging
by: Yi, Weixi, et al.
Published: (2024)

GUSL: A Novel and Efficient Machine Learning Model for Prostate Segmentation on MRI
by: Yang, Jiaxin, et al.
Published: (2025)

Do High-Performance Image-to-Image Translation Networks Enable the Discovery of Radiomic Features? Application to MRI Synthesis from Ultrasound in Prostate Cancer
by: Salmanpour, Mohammad R., et al.
Published: (2024)

Ultra-Strong Gradient Diffusion MRI with Self-Supervised Learning for Prostate Cancer Characterization
by: Patil, Tanishq, et al.
Published: (2025)

PGDiffSeg: Prior-Guided Denoising Diffusion Model with Parameter-Shared Attention for Breast Cancer Segmentation
by: Feng, Feiyan, et al.
Published: (2024)

SegRet: An Efficient Design for Semantic Segmentation with Retentive Network
by: Li, Zhiyuan, et al.
Published: (2025)

RadHop-Net: A Lightweight Radiomics-to-Error Regression for False Positive Reduction In MRI Prostate Cancer Detection
by: Magoulianitis, Vasileios, et al.
Published: (2025)

Digital Volumetric Biopsy Cores Improve Gleason Grading of Prostate Cancer Using Deep Learning
by: Redekop, Ekaterina, et al.
Published: (2024)

TRUSWorthy: Toward Clinically Applicable Deep Learning for Confident Detection of Prostate Cancer in Micro-Ultrasound
by: Harmanani, Mohamed, et al.
Published: (2025)

Hierarchical SegNet with Channel and Context Attention for Accurate Lung Segmentation in Chest X-ray Images
by: Khaniki, Mohammad Ali Labbaf, et al.
Published: (2024)

Adaptive Voxel-Weighted Loss Using L1 Norms in Deep Neural Networks for Detection and Segmentation of Prostate Cancer Lesions in PET/CT Images
by: Dzikunu, Obed Korshie, et al.
Published: (2025)

UNIR-Net: A Novel Approach for Restoring Underwater Images with Non-Uniform Illumination Using Synthetic Data
by: Perez-Zarate, Ezequiel, et al.
Published: (2025)

Benchmarking Image Transformers for Prostate Cancer Detection from Ultrasound Data
by: Harmanani, Mohamed, et al.
Published: (2024)

Domain Transfer Through Image-to-Image Translation for Uncertainty-Aware Prostate Cancer Classification
by: Zhou, Meng, et al.
Published: (2023)

DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling
by: Ji, Hangyu
Published: (2025)

MedSegNet10: A Publicly Accessible Network Repository for Split Federated Medical Image Segmentation
by: Shiranthika, Chamani, et al.
Published: (2025)

SegNet: A Segmented Deep Learning based Convolutional Neural Network Approach for Drones Wildfire Detection
by: Jonnalagadda, Aditya V., et al.
Published: (2024)

RamanSeg: Interpretability-driven Deep Learning on Raman Spectra for Cancer Diagnosis
by: Tomy, Chris, et al.
Published: (2026)

Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer
by: Shaik, Abdul Samad, et al.
Published: (2025)

MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance
by: Wong, Hallee E., et al.
Published: (2024)

SmoothSegNet: A Global-Local Framework for Liver Tumor Segmentation with Clinical KnowledgeInformed Label Smoothing
by: Wang, Hairong, et al.
Published: (2024)

TextDiffSeg: Text-guided Latent Diffusion Model for 3d Medical Images Segmentation
by: Ma, Kangbo
Published: (2025)

BreastSegNet: Multi-label Segmentation of Breast MRI
by: Li, Qihang, et al.
Published: (2025)

MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization
by: Bi, Yuan, et al.
Published: (2023)

SegImgNet: Segmentation-Guided Dual-Branch Network for Retinal Disease Diagnoses
by: Luo, Xinwei, et al.
Published: (2025)