Recent advances and clinical applications of deep learning in medical image analysis
Deep learning has received extensive research interest in developing new medical image
processing algorithms, and deep learning based models have been remarkably successful …
processing algorithms, and deep learning based models have been remarkably successful …
Multi-task deep learning for medical image computing and analysis: A review
The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …
conventional deep learning models are constructed for a single specific task, multi-task deep …
A survey on incorporating domain knowledge into deep learning for medical image analysis
Although deep learning models like CNNs have achieved great success in medical image
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
analysis, the small size of medical datasets remains a major bottleneck in this area. To …
Lvit: language meets vision transformer in medical image segmentation
Deep learning has been widely used in medical image segmentation and other aspects.
However, the performance of existing medical image segmentation models has been limited …
However, the performance of existing medical image segmentation models has been limited …
Learning from multiple datasets with heterogeneous and partial labels for universal lesion detection in CT
Large-scale datasets with high-quality labels are desired for training accurate deep learning
models. However, due to the annotation cost, datasets in medical imaging are often either …
models. However, due to the annotation cost, datasets in medical imaging are often either …
DeepTarget: Gross tumor and clinical target volume segmentation in esophageal cancer radiotherapy
Gross tumor volume (GTV) and clinical target volume (CTV) delineation are two critical steps
in the cancer radiotherapy planning. GTV defines the primary treatment area of the gross …
in the cancer radiotherapy planning. GTV defines the primary treatment area of the gross …
Toward high-throughput artificial intelligence-based segmentation in oncological PET imaging
An array of artificial intelligence (AI) techniques in the field of medical imaging has emerged
in the past decade for automated image segmentation. 1 Medical image segmentation seeks …
in the past decade for automated image segmentation. 1 Medical image segmentation seeks …
Global-Local attention network with multi-task uncertainty loss for abnormal lymph node detection in MR images
Accurate and reliable detection of abnormal lymph nodes in magnetic resonance (MR)
images is very helpful for the diagnosis and treatment of numerous diseases. However, it is …
images is very helpful for the diagnosis and treatment of numerous diseases. However, it is …
Weakly-supervised universal lesion segmentation with regional level set loss
Accurately segmenting a variety of clinically significant lesions from whole body computed
tomography (CT) scans is a critical task on precision oncology imaging, denoted as …
tomography (CT) scans is a critical task on precision oncology imaging, denoted as …
Mediastinal lymph node detection and segmentation using deep learning
Automatic lymph node (LN) segmentation and detection for cancer staging are critical. In
clinical practice, computed tomography (CT) and positron emission tomography (PET) …
clinical practice, computed tomography (CT) and positron emission tomography (PET) …