A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned
The successful early diagnosis of brain tumors plays a major role in improving the treatment
outcomes and thus improving patient survival. Manually evaluating the numerous magnetic …
outcomes and thus improving patient survival. Manually evaluating the numerous magnetic …
Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging
D García-Lorenzo, S Francis, S Narayanan… - Medical image …, 2013 - Elsevier
Magnetic resonance (MR) imaging is often used to characterize and quantify multiple
sclerosis (MS) lesions in the brain and spinal cord. The number and volume of lesions have …
sclerosis (MS) lesions in the brain and spinal cord. The number and volume of lesions have …
Medical big data: neurological diseases diagnosis through medical data analysis
Diagnosis of neurological diseases is a growing concern and one of the most difficult
challenges for modern medicine. According to the World Health Organisation's recent report …
challenges for modern medicine. According to the World Health Organisation's recent report …
[HTML][HTML] Slowly expanding lesions relate to persisting black-holes and clinical outcomes in relapse-onset multiple sclerosis
Abstract Background Slowly expanding lesions (SELs) are MRI markers of chronic active
lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in …
lesions in multiple sclerosis (MS). T1-hypointense black holes, and reductions in …
Glioma detection on brain MRIs using texture and morphological features with ensemble learning
The real time usage of Computer Aided Diagnosis (CAD) systems to detect brain tumors as
proposed in the literature is yet to be explored. Gliomas are the most commonly found brain …
proposed in the literature is yet to be explored. Gliomas are the most commonly found brain …
Segmentation of multiple sclerosis lesions in MR images: a review
Introduction Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts
of the nervous system through the lesions generated in the white matter of the brain. It brings …
of the nervous system through the lesions generated in the white matter of the brain. It brings …
[HTML][HTML] Boosting multiple sclerosis lesion segmentation through attention mechanism
Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis
and monitoring its progression. Although several attempts have been made to segment …
and monitoring its progression. Although several attempts have been made to segment …
Automatic diagnosis of neurological diseases using MEG signals with a deep neural network
The application of deep learning to neuroimaging big data will help develop computer-aided
diagnosis of neurological diseases. Pattern recognition using deep learning can extract …
diagnosis of neurological diseases. Pattern recognition using deep learning can extract …
[HTML][HTML] Rotation-invariant multi-contrast non-local means for MS lesion segmentation
Multiple sclerosis (MS) lesion segmentation is crucial for evaluating disease burden,
determining disease progression and measuring the impact of new clinical treatments. MS …
determining disease progression and measuring the impact of new clinical treatments. MS …
Brain tumor detection with integrating traditional and computational intelligence approaches across diverse imaging modalities-Challenges and future directions
Brain tumor segmentation and classification play a crucial role in the diagnosis and
treatment planning of brain tumors. Accurate and efficient methods for identifying tumor …
treatment planning of brain tumors. Accurate and efficient methods for identifying tumor …