Medical Image
Medical image analysis focuses on extracting meaningful information from various imaging modalities (e.g., CT, MRI, X-ray) to improve diagnosis and treatment planning. Current research emphasizes developing robust and efficient algorithms, often employing convolutional neural networks (CNNs), transformers, and diffusion models, to address challenges like data variability, limited annotations, and privacy concerns. These advancements are crucial for improving the accuracy and speed of medical image analysis, leading to better patient care and accelerating medical research.
Papers
Parameter choices in HaarPSI for IQA with medical images
Clemens Karner, Janek Gröhl, Ian Selby, Judith Babar, Jake Beckford, Thomas R Else, Timothy J Sadler, Shahab Shahipasand, Arthikkaa Thavakumar, Michael Roberts, James H.F. Rudd, Carola-Bibiane Schönlieb, Jonathan R Weir-McCall, Anna Breger
Denoising Diffusion Models for Anomaly Localization in Medical Images
Cosmin I. Bercea, Philippe C. Cattin, Julia A. Schnabel, Julia Wolleb
Less is More: Selective Reduction of CT Data for Self-Supervised Pre-Training of Deep Learning Models with Contrastive Learning Improves Downstream Classification Performance
Daniel Wolf, Tristan Payer, Catharina Silvia Lisson, Christoph Gerhard Lisson, Meinrad Beer, Michael Götz, Timo Ropinski
Deep Learning Applications in Medical Image Analysis: Advancements, Challenges, and Future Directions
Aimina Ali Eli, Abida Ali
Deep Generative Models Unveil Patterns in Medical Images Through Vision-Language Conditioning
Xiaodan Xing, Junzhi Ning, Yang Nan, Guang Yang
Can Medical Vision-Language Pre-training Succeed with Purely Synthetic Data?
Che Liu, Zhongwei Wan, Haozhe Wang, Yinda Chen, Talha Qaiser, Chen Jin, Fariba Yousefi, Nikolay Burlutskiy, Rossella Arcucci
Synthetic Augmentation for Anatomical Landmark Localization using DDPMs
Arnela Hadzic, Lea Bogensperger, Simon Johannes Joham, Martin Urschler
Advancing Healthcare: Innovative ML Approaches for Improved Medical Imaging in Data-Constrained Environments
Al Amin, Kamrul Hasan, Saleh Zein-Sabatto, Liang Hong, Sachin Shetty, Imtiaz Ahmed, Tariqul Islam
Large-Scale 3D Medical Image Pre-training with Geometric Context Priors
Linshan Wu, Jiaxin Zhuang, Hao Chen
Improving Colorectal Cancer Screening and Risk Assessment through Predictive Modeling on Medical Images and Records
Shuai Jiang, Christina Robinson, Joseph Anderson, William Hisey, Lynn Butterly, Arief Suriawinata, Saeed Hassanpour