PURPOSE: The purpose of this study was to propose a method for segmentation and volume measurement of graft liver and spleen of pediatric transplant recipients on digital imaging and communications in medicine (DICOM) -format images using U-Net and t...
Deep learning has attracted great attention in the medical imaging community as a promising solution for automated, fast and accurate medical image analysis, which is mandatory for quality healthcare. Convolutional neural networks and its variants ha...
BACKGROUND: This paper endeavors to identify an expedient approach for the detection of the brain tumor in MRI images. The detection of tumor is based on i) review of the machine learning approach for the identification of brain tumor and ii) review ...
BACKGROUND: Medical image fusion is very important for the diagnosis and treatment of diseases. In recent years, there have been a number of different multi-modal medical image fusion algorithms that can provide delicate contexts for disease diagnosi...
Nuclear medicine review. Central & Eastern Europe
Jan 1, 2020
In recent years, processing of the imaging signal derived from CT, MR or positron emission has proven to be able to predict outcome parameters in cancer patients. The processing techniques of the signal constitute the discipline of radiomics. The qua...
BACKGROUND: Glioma is one of the most common and aggressive primary brain tumors that endanger human health. Tumors segmentation is a key step in assisting the diagnosis and treatment of cancer disease. However, it is a relatively challenging task to...
BACKGROUND: In this study, a novel and fully automatic skin disease classification approach is proposed using statistical feature extraction and Artificial Neural Network (ANN) based classification using first and second order statistical moments, th...
PURPOSE: Parkinson's disease (PD), which is the second most common neurodegenerative disease following Alzheimer's disease, can be diagnosed clinically when about 70% of the dopaminergic neurons are lost and symptoms are noticed. Neuroimaging methods...
OBJECTIVE: To estimate the possibility of diagnosis of malignant pleural effusion using convolutional neural networks of facies images of pleural exudates obtained by the method of wedge-shaped dehydration.
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