The thyroid is one of the largest endocrine glands in the human body, which is involved in several body mechanisms like controlling protein synthesis and the body's sensitivity to other hormones and use of energy sources. Hence, it is of prime import...
Superresolution localization microscopy strongly relies on robust identification algorithms for accurate reconstruction of the biological systems it is used to measure. The fields of machine learning and computer vision have provided promising soluti...
OBJECTIVE: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predicti...
International journal of neural systems
Sep 20, 2018
The early detection of Alzheimer's disease and quantification of its progression poses multiple difficulties for machine learning algorithms. Two of the most relevant issues are related to missing data and results interpretability. To deal with both ...
The Clinical Oncology of American Society report in 2016 predicted deaths are increased upto 9570 due to oral cancer. This cancer occurs due to abnormal tissue growth in the oral cavity. This cancer has limited symptoms, so, it has been difficult to ...
PURPOSE: Intensity modulated radiation therapy (IMRT) is commonly employed for treating head and neck (H&N) cancer with uniform tumor dose and conformal critical organ sparing. Accurate delineation of organs-at-risk (OARs) on H&N CT images is thus es...
PURPOSE: The purpose of this study was the evaluation of anthropomorphic model observers trained with neural networks for the prediction of a human observer's performance.
PURPOSE: We sought to assess whether machine learning-based classification approaches can improve the classification of pancreatic tumor models relative to more simplistic analysis methods, using T relaxation, CEST, and DCE MRI.
The purpose of the work is to develop a deep unsupervised learning strategy for cone-beam CT (CBCT) to CT deformable image registration (DIR). This technique uses a deep convolutional inverse graphics network (DCIGN) based DIR algorithm implemented o...
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