Hepatocellular carcinoma (HCC) can be potentially discovered from abdomi...
Measuring lesion size is an important step to assess tumor growth and mo...
Accurately segmenting a variety of clinically significant lesions from w...
Using radiological scans to identify liver tumors is crucial for proper
...
Monitoring treatment response in longitudinal studies plays an important...
Radiological images such as computed tomography (CT) and X-rays render
a...
Large-scale datasets with high-quality labels are desired for training
a...
Mask-based annotation of medical images, especially for 3D data, is a
bo...
Identifying, measuring and reporting lesions accurately and comprehensiv...
Determining the spread of GTV_LN is essential in defining the respective...
Although having achieved great success in medical image segmentation, de...
Effective and non-invasive radiological imaging based tumor/lesion
chara...
Lesion detection is an important problem within medical imaging analysis...
Finding and identifying scatteredly-distributed, small, and critically
i...
In medical imaging, organ/pathology segmentation models trained on curre...
Acquiring large-scale medical image data, necessary for training machine...
Automatic segmentation of abdomen organs using medical imaging has many
...
We propose a novel framework, uncertainty-aware multi-view co-training
(...
Automated lesion segmentation from computed tomography (CT) is an import...
Given image labels as the only supervisory signal, we focus on harvestin...
Volumetric lesion segmentation from computed tomography (CT) images is a...
Automatic pancreas segmentation in radiology images, eg., computed tomog...
Volumetric lesion segmentation via medical imaging is a powerful means t...
Deep neural networks have demonstrated very promising performance on acc...