Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many different 2D medical image analysis tasks. In clinical practice, however, a large part of the medical imaging data available is in 3D, e.g, magnetic resonance ima...
International journal of radiation oncology, biology, physics
Jun 13, 2019
PURPOSE: Deep learning is an emerging technique that allows us to capture imaging information beyond the visually recognizable level of a human being. Because of the anatomic characteristics and location, on-board target verification for radiation de...
The segmentation of pancreas is important for medical image analysis, yet it faces great challenges of class imbalance, background distractions, and non-rigid geometrical features. To address these difficulties, we introduce a deep Q network (DQN) dr...
AIM: Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important.
IEEE journal of biomedical and health informatics
Jan 9, 2019
Accurate and automatic organ segmentation is critical for computer-aided analysis towards clinical decision support and treatment planning. State-of-the-art approaches have achieved remarkable segmentation accuracy on large organs, such as the liver ...
Single-cell RNA sequencing (scRNA-seq) is an emerging technology for profiling the gene expression of thousands of cells at the single cell resolution. Currently, the labeling of cells in an scRNA-seq dataset is performed by manually characterizing c...
International journal of computer assisted radiology and surgery
May 30, 2018
PURPOSE: Deep convolutional neural networks (DCNN) are currently ubiquitous in medical imaging. While their versatility and high-quality results for common image analysis tasks including segmentation, localisation and prediction is astonishing, the l...
BACKGROUND: Efficient computational recognition and segmentation of target organ from medical images are foundational in diagnosis and treatment, especially about pancreas cancer. In practice, the diversity in appearance of pancreas and organs in abd...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 16, 2018
Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of volumetric images. In this work, we show that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical st...
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis. Specifically, as a small, soft, and flexible abdominal organ, the pancreas demonstrates very high inter-patient a...
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