Missing data is a common problem in longitudinal studies due to subject dropouts and failed scans. We present a graph-based convolutional neural network to predict missing diffusion MRI data. In particular, we consider the relationships between sampl...
We aimed to assess feasibility of a support vector machine (SVM) texture classifier to discriminate pathologic infiltration patterns from the normal bone marrows in MRI. This retrospective study included 467 cases, which were split into a training (n...
IEEE transactions on neural networks and learning systems
Apr 11, 2019
The pulse-coupled neural network (PCNN) model is a third-generation artificial neural network without training that uses the synchronous pulse bursts of neurons to process digital images, but the lack of in-depth theoretical research limits its exten...
This paper introduces a deep-learning based computer-aided diagnostic (CAD) system for the early detection of acute renal transplant rejection. For noninvasive detection of kidney rejection at an early stage, the proposed CAD system is based on the f...
PURPOSE: Radiomics allows for powerful data-mining and feature extraction techniques to guide clinical decision making. Image segmentation is a necessary step in such pipelines and different techniques can significantly affect results. We demonstrate...
Australasian physical & engineering sciences in medicine
Apr 8, 2019
This study aims to develop a semi-automatic system for brain tumor segmentation in 3D MR images. For a given image, noise was corrected using SUSAN algorithm first. A specific region of interest (ROI) that contains tumor was identified and then the i...
For quantitative neuroimaging studies using multi-echo gradient echo (mGRE) images, additional T-weighted magnetization prepared rapid gradient echo (MPRAGE) images are often acquired to supplement the insufficient morphometric information of mGRE fo...
PURPOSE: While MRI is the modality of choice for the assessment of patients with brain tumors, differentiation between various tumors based on their imaging characteristics might be challenging due to overlapping imaging features. The purpose of this...
BACKGROUND: The Response Assessment in Neuro-Oncology (RANO) criteria and requirements for a uniform protocol have been introduced to standardise assessment of MRI scans in both clinical trials and clinical practice. However, these criteria mainly re...
IEEE journal of biomedical and health informatics
Apr 1, 2019
Automatic polyp detection has been shown to be difficult due to various polyp-like structures in the colon and high interclass variations in polyp size, color, shape, and texture. An efficient method should not only have a high correct detection rate...
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