International journal of radiation oncology, biology, physics
Jul 2, 2022
PURPOSE: Deep learning-based algorithms have been shown to be able to automatically detect and segment brain metastases (BMs) in magnetic resonance imaging, mostly based on single-institutional data sets. This work aimed to investigate the use of dee...
IEEE journal of biomedical and health informatics
Jul 1, 2022
Semi-supervised learning has substantially advanced medical image segmentation since it alleviates the heavy burden of acquiring the costly expert-examined annotations. Especially, the consistency-based approaches have attracted more attention for th...
Computational and mathematical methods in medicine
Jul 1, 2022
Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important tasks for neurologists and radiologists is to detect brain tumors early. Recent claims have been made that computer-aided diagnosis-based systems can ...
Topics in magnetic resonance imaging : TMRI
Jun 28, 2022
OBJECTIVES: Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remar...
Computational intelligence and neuroscience
Jun 27, 2022
In this paper, an autonomous brain tumor segmentation and detection model is developed utilizing a convolutional neural network technique that included a local binary pattern and a multilayered support vector machine. The detection and classification...
Glioma is the most aggressive and dangerous primary brain tumor with a survival time of less than 14 months. Segmentation of tumors is a necessary task in the image processing of the gliomas and is important for its timely diagnosis and starting a tr...
Computational intelligence and neuroscience
Jun 24, 2022
Given the need for quantitative measurement and 3D visualisation of brain tumours, more and more attention has been paid to the automatic segmentation of tumour regions from brain tumour magnetic resonance (MR) images. In view of the uneven grey dist...
Computational and mathematical methods in medicine
Jun 20, 2022
As the most prevalent and deadly malignancy, brain tumors have a dismal survival rate when they are at their most hazardous. Using mostly traditional medical image processing methods, segmenting and classifying brain malignant tumors is a challenging...
BACKGROUND: Real-world data (RWD) is increasingly being embraced as an invaluable source of information to address clinical and policy-relevant questions that are unlikely to ever be answered by clinical trials. However, the largely unrealised potent...