Automatic 3D pulmonary nodule detection in CT images: a survey

IRS Valente, PC Cortez, EC Neto, JM Soares… - Computer methods and …, 2016 - Elsevier
This work presents a systematic review of techniques for the 3D automatic detection of
pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze …

A comprehensive survey on the detection, classification, and challenges of neurological disorders

AA Lima, MF Mridha, SC Das, MM Kabir, MR Islam… - Biology, 2022 - mdpi.com
Simple Summary This study represents a resourceful review article that can deliver
resources on neurological diseases and their implemented classification algorithms to …

Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm

ESA El-Dahshan, HM Mohsen, K Revett… - Expert systems with …, 2014 - Elsevier
Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic capabilities
of physicians and reduce the time required for accurate diagnosis. The objective of this …

Medical big data: neurological diseases diagnosis through medical data analysis

S Siuly, Y Zhang - Data Science and Engineering, 2016 - Springer
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 …

Automatic nodule detection for lung cancer in CT images: A review

G Zhang, S Jiang, Z Yang, L Gong, X Ma, Z Zhou… - Computers in biology …, 2018 - Elsevier
Automatic lung nodule detection has great significance for treating lung cancer and
increasing patient survival. This work summarizes a critical review of recent techniques for …

Computer-aided detection system for lung cancer in computed tomography scans: review and future prospects

M Firmino, AH Morais, RM Mendoça… - Biomedical engineering …, 2014 - Springer
Introduction The goal of this paper is to present a critical review of major Computer-Aided
Detection systems (CADe) for lung cancer in order to identify challenges for future research …

Studying autism spectrum disorder with structural and diffusion magnetic resonance imaging: a survey

MMT Ismail, RS Keynton, MMMO Mostapha… - Frontiers in human …, 2016 - frontiersin.org
Magnetic resonance imaging (MRI) modalities have emerged as powerful means that
facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their …

Application of machine and deep learning algorithms in optical microscopic detection of Plasmodium: A malaria diagnostic tool for the future

C Ikerionwu, C Ugwuishiwu, I Okpala, I James… - Photodiagnosis and …, 2022 - Elsevier
Abstract Machine and deep learning techniques are prevalent in the medical discipline due
to their high level of accuracy in disease diagnosis. One such disease is malaria caused by …

Automated detection of multiple sclerosis lesions in serial brain MRI

X Lladó, O Ganiler, A Oliver, R Martí, J Freixenet… - Neuroradiology, 2012 - Springer
Introduction Multiple sclerosis (MS) is a serious disease typically occurring in the brain
whose diagnosis and efficacy of treatment monitoring are vital. Magnetic resonance imaging …

Automatic diagnosis of neurological diseases using MEG signals with a deep neural network

J Aoe, R Fukuma, T Yanagisawa, T Harada… - Scientific reports, 2019 - nature.com
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 …