Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 16, 2021
Fetal echocardiography is an essential and comprehensive examination technique for the detection of fetal heart anomalies. Accurate cardiac chambers segmentation can assist cardiologists to analyze cardiac morphology and facilitate heart disease diag...
Earthworms (Crassiclitellata) being ecosystem engineers significantly affect the physical, chemical, and biological properties of the soil by recycling organic material, increasing nutrient availability, and improving soil structure. The efficiency o...
Computer methods and programs in biomedicine
Sep 15, 2021
BACKGROUND AND OBJECTIVE: Aortic dissection is a severe cardiovascular pathology in which an injury of the intimal layer of the aorta allows blood flowing into the aortic wall, forcing the wall layers apart. Such situation presents a high mortality r...
Recently,deep learning (DL)-based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by grouping the...
Segmentation of retinal vessels is a critical step for the diagnosis of some fundus diseases. To further enhance the performance of vessel segmentation, we propose a method based on a gated skip-connection network with adaptive upsampling (GSAU-Net)...
Since whole-slide imaging has been commercially available for over 2 decades, digital pathology has become a constantly expanding aspect of the pathology profession that will continue to significantly impact how pathologists conduct their craft. Whil...
In the last two decades, neuroscience has produced intriguing evidence for a central role of the claustrum in mammalian forebrain structure and function. However, relatively few in vivo studies of the claustrum exist in humans. A reason for this may ...
PURPOSE: Deep learning has achieved impressive performance across a variety of tasks, including medical image processing. However, recent research has shown that deep neural networks (DNNs) are susceptible to small adversarial perturbations in the im...
Volumetric imaging of dynamic signals in a large, moving, and light-scattering specimen is extremely challenging, owing to the requirement on high spatiotemporal resolution and difficulty in obtaining high-contrast signals. Here we report that throug...
To investigate the impact of training sample size on the performance of deep learning-based organ auto-segmentation for head-and-neck cancer patients, a total of 1160 patients with head-and-neck cancer who received radiotherapy were enrolled in this ...
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