Brain tumor segmentation and classification from magnetic resonance images: Review of selected methods from 2014 to 2019

A Tiwari, S Srivastava, M Pant - Pattern recognition letters, 2020 - Elsevier
The past few years have witnessed a significant increase in medical cases related to brain
tumors, making it the 10th most common form of tumor affecting children and adults alike …

Deep transfer learning approaches in performance analysis of brain tumor classification using MRI images

C Srinivas, NP KS, M Zakariah… - Journal of …, 2022 - Wiley Online Library
Brain tumor classification is a very important and the most prominent step for assessing life‐
threatening abnormal tissues and providing an efficient treatment in patient recovery. To …

Vgg-scnet: A vgg net-based deep learning framework for brain tumor detection on mri images

MS Majib, MM Rahman, TMS Sazzad, NI Khan… - IEEE …, 2021 - ieeexplore.ieee.org
A brain tumor is a life-threatening neurological condition caused by the unregulated
development of cells inside the brain or skull. The death rate of people with this condition is …

A Review of Computational Intelligence Models for Brain Tumour Classification and Prediction

JK Appati, GA Brown, MAT Soli… - International Journal of …, 2021 - igi-global.com
This review aims to systematically analyze ML models from four aspects: type of ML
technique, estimation accuracy, model comparison, and estimation context. A systematic …

[HTML][HTML] Automatic quality assessment for 2D fetal sonographic standard plane based on multitask learning

B Zhang, H Liu, H Luo, K Li - Medicine, 2021 - journals.lww.com
The quality control of fetal sonographic (FS) images is essential for the correct biometric
measurements and fetal anomaly diagnosis. However, quality control requires professional …

[PDF][PDF] Brain tumors classification with deep learning using data augmentation

K Gürkahraman, R Karakiş - Journal of the Faculty of Engineering …, 2021 - researchgate.net
Purpose: In this study, the essential aims are the classification of brain tumors on the
figshare dataset; determination of which axial, coronal, and sagittal MR plane slices is …

An Adaptive Eroded Deep Convolutional neural network for brain image segmentation and classification using Inception ResnetV2

GS Sunsuhi, SA Jose - Biomedical Signal Processing and Control, 2022 - Elsevier
In today's scenario, the main challenging issue in medical field is the tumor detection in
human brain. An uncontrolled growth of abnormal nerve tissues contributes to brain tumor …

A Bibliometric review: brain tumor magnetic resonance imagings using different convolutional neural network architectures

A Rath, DK Mohanty, BSP Mishra, DK Bagal - World Neurosurgery, 2023 - Elsevier
Background Numerous scientists and researchers have been developing advanced
procedures and methods for diagnosing the kind and phase of a human tumor. Brain tumors …

A review and analysis of IoT and machine learning algorithms in the brain disease diagnosis and detection

R Chahar, AK Dubey - ECS Transactions, 2022 - iopscience.iop.org
In this paper a review and analysis were performed based on the Internet of Things (IoT) and
machine learning algorithms for the brain disease diagnosis and detection. This paper …

Brain Tumor Detection that uses CNN in MRI

N Molachan, KC Manoj… - 2021 Asian Conference on …, 2021 - ieeexplore.ieee.org
Brain cyst is a mass of unnecessary units growing in the brain or the multiplication of normal
or abnormal cells that are not essential for the brain, which may even be the cause for death …