A new approach of brain MRI analysis for identifying Creutzfeldt-Jakob disease (CJD)

Islam, Akib Jayed; Ahammad, Khandoker Tanjim; Barua, Bithi; Alam, Shazia; Biswas, Akash

doi:10.1109/eict.2017.8275191

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Pixel counting approach is another way to analysis the brain tissue. In [41], used MRI head scans to determine caudate and putamen for identifying the existence of brain tissue of Creutzfeldt-Jakob Disease (CJD) with the help of pixel counting approach through analyzing the image block by block, and three stages image segmentation.…”

Section: A Mri Modalitiesmentioning

confidence: 99%

Neuroimaging and Machine Learning for Dementia Diagnosis: Recent Advancements and Future Prospects

Ahmed

Zhang

Feng

et al. 2019

IEEE Rev. Biomed. Eng.

101

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Dementia, a chronic and progressive cognitive declination of brain function due to disease or impairment, is becoming more prevalent due to the aging population. A major challenge in dementia is achieving the accurate and timely diagnosis. In recent years, neuroimaging with computer-aided algorithms have made remarkable advances in addressing this challenge. Much of the success of these approaches can be attributed to the application of machine learning and deep learning techniques for neuroimaging. In this review paper, we present a comprehensive survey of automated diagnostic approaches for dementia using medical image analysis and machine learning algorithms published in the previous five years (2013-2018). Based on the rigorous review of the existing works, we have found that while most of the studies focused on Alzheimer's disease have demonstrated reasonable performance, the identification of other types of dementia remains a major challenge. Hybrid imaging analysis through deep learning approaches may hold promises for early diagnosis of these other types of dementia, and warrant further investigation in the future. The main contributions of this review paper are as follows: 1. Based on the detailed analysis of the existing literature, this paper discusses the most recent neuroimaging procedures for dementia diagnosis, and 2. It systematically explains the machine learning techniques and, in particular, deep learning approaches for early detection of dementia.

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Section: A Mri Modalitiesmentioning

confidence: 99%

Neuroimaging and Machine Learning for Dementia Diagnosis: Recent Advancements and Future Prospects

Ahmed

Zhang

Feng

et al. 2019

IEEE Rev. Biomed. Eng.

101

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A Systematic Review and Implementation of IoT-Based Pervasive Sensor-Enabled Tracking System for Dementia Patients

Ray

Dash

2019

J Med Syst

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Medical Imaging Using Deep Learning

Jayan¹,

Fathima²,

Nazarulla³

et al. 2022

2022 International Conference on Innovations in Science and Technology for Sustainable Development (ICISTSD)

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The healthcare sector has been transformed by deep learning, a kind of artificial intelligence Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are two examples of deep learning techniques that have been used to evaluate medical pictures, forecast illness outcomes, and enhance patient care. This study examines the important strides made by deep learning in the fields of radiology, pathology, genomics, and electronic health records (EHRs). Additionally, it draws attention to the difficulties and moral issues that come with the application of deep learning in healthcare, highlighting the necessity of strong data protection and model interpretability. Deep learning's potential and promising results in healthcare highlight its revolutionary effects on patient care, diagnosis, and treatment, ultimately raising the standard of care.

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A new approach of brain MRI analysis for identifying Creutzfeldt-Jakob disease (CJD)

Cited by 3 publications

References 12 publications

Neuroimaging and Machine Learning for Dementia Diagnosis: Recent Advancements and Future Prospects

Neuroimaging and Machine Learning for Dementia Diagnosis: Recent Advancements and Future Prospects

A Systematic Review and Implementation of IoT-Based Pervasive Sensor-Enabled Tracking System for Dementia Patients

Medical Imaging Using Deep Learning

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