4.8k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of GroningenNL38 papers
- University Hospital of GenevaCH6 papers
- University of Southern DenmarkDK6 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Radboud University Medical CenterNL5 papers
- Radboud University NijmegenNL5 papers
- InsermFR4 papers
- Iran University of Medical SciencesIR4 papers
- Stanford UniversityUS4 papers
- University College LondonGB4 papers
- University Medical Center UtrechtNL4 papers
- University of British ColumbiaCA4 papers
5 papers · 1 filter
Path and Bone-Contour Regularized Unpaired MRI-to-CT Translation
Teng Zhou, Jax Luo, Yuping Sun +4
Accurate MRI-to-CT translation promises the integration of complementary imaging information without the need for additional imaging sessions. Given the practical challenges associ…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…
Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey
Anusha Aswath, Ahmad Alsahaf, Ben N. G. Giepmans +1
Automated and semi-automated techniques in biomedical electron microscopy (EM) enable the acquisition of large datasets at a high rate. Segmentation methods are therefore essential…
CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification
Zhibin Liao, Kewen Liao, Haifeng Shen +6
Convolutional neural networks (CNNs) have gained significant popularity in orthopedic imaging in recent years due to their ability to solve fracture classification problems. A comm…
Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection
Sunyi Zheng, Jiapan Guo, Xiaonan Cui +3
Accurate pulmonary nodule detection is a crucial step in lung cancer screening. Computer-aided detection (CAD) systems are not routinely used by radiologists for pulmonary nodule d…