Mitochondrial morphological defects are a common feature of diseased cardiac myocytes. However, quantitative assessment of mitochondrial morphology is limited by the time-consuming manual segmentation of electron micrograph (EM) images. To advance un...
Medical image fusion technology synthesizes complementary information from multimodal medical images. This technology is playing an increasingly important role in clinical applications. In this paper, we propose a new convolutional neural network, wh...
Computer-Aided Diagnosis (CAD) for dermatological diseases offers one of the most notable showcases where deep learning technologies display their impressive performance in acquiring and surpassing human experts. In such the CAD process, a critical s...
Developing a convolutional neural network (CNN) for medical image segmentation is a complex task, especially when dealing with the limited number of available labelled medical images and computational resources. This task can be even more difficult i...
In the era of data-driven medicine, rapid access and accurate interpretation of medical images are becoming increasingly important. The DICOM Image ANalysis and Archive (DIANA) system is an open-source, lightweight, and scalable Python interface that...
Custom inspection using X-ray imaging is a very promising application of modern pattern recognition technology. However, the lack of data or renewal of tariff items makes the application of such technology difficult. In this paper, we present a data ...
PURPOSE: To investigate multiple deep learning methods for automated segmentation (auto-segmentation) of the parotid glands, submandibular glands, and level II and level III lymph nodes on magnetic resonance imaging (MRI). Outlining radiosensitive or...
PURPOSE: Cerebrovascular segmentation in magnetic resonance imaging (MRI) plays an important role in the diagnosis and treatment of cerebrovascular diseases. Many segmentation frameworks based on convolutional neural networks (CNNs) or U-Net-like str...
The speed and accuracy of phenotype detection from medical images are some of the most important qualities needed for any informed and timely response such as early detection of cancer or detection of desirable phenotypes for animal breeding. To impr...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Oct 30, 2021
Whole-brain segmentation is a crucial pre-processing step for many neuroimaging analyses pipelines. Accurate and efficient whole-brain segmentations are important for many neuroimage analysis tasks to provide clinically relevant information. Several ...
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