Neural networks : the official journal of the International Neural Network Society
Dec 17, 2019
Compressed sensing (CS) significantly accelerates magnetic resonance imaging (MRI) by allowing the exact reconstruction of image from highly undersampling k-space data. In this process, the high sparsity obtained by the learned dictionary and exploit...
A brain tumor is a mass that grows unevenly in the brain and directly affects human life. This mass occurs spontaneously because of the tissues surrounding the brain or the skull. Surgical methods are generally preferred for the treatment of the brai...
Brain tumor detection depicts a tough job because of its shape, size and appearance variations. In this manuscript, a deep learning model is deployed to predict input slices as a tumor (unhealthy)/non-tumor (healthy). This manuscript employs a high p...
Magnetic resonance electrical properties tomography (MR-EPT) is a technique used to estimate the conductivity and permittivity of tissues from MR measurements of the transmit magnetic field. Different reconstruction methods are available; however, al...
IEEE journal of biomedical and health informatics
Dec 16, 2019
Segmentation of prostate in medical imaging data (e.g., CT, MRI, TRUS) is often considered as a critical yet challenging task for radiotherapy treatment. It is relatively easier to segment prostate from MR images than from CT images, due to better so...
As a promising method in artificial intelligence, deep learning has been proven successful in several domains ranging from acoustics and images to natural language processing. With medical imaging becoming an important part of disease screening and d...
The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radio...
Neural networks : the official journal of the International Neural Network Society
Dec 16, 2019
The efforts devoted to manually increasing the width and depth of convolutional neural network (CNN) usually require a large amount of time and expertise. It has stimulated a rising demand of neural architecture search (NAS) over these years. However...
Computational intelligence and neuroscience
Dec 16, 2019
This study develops tomato disease detection methods based on deep convolutional neural networks and object detection models. Two different models, Faster R-CNN and Mask R-CNN, are used in these methods, where Faster R-CNN is used to identify the typ...
The importance of T cells in immunotherapy has motivated developing technologies to improve therapeutic efficacy. One objective is assessing antigen-induced T cell activation because only functionally active T cells are capable of killing the desired...
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