[HTML][HTML] Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges
T Saba - Journal of infection and public health, 2020 - Elsevier
Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
Computer vision for microscopic skin cancer diagnosis using handcrafted and non‐handcrafted features
T Saba - Microscopy Research and Technique, 2021 - Wiley Online Library
Skin covers the entire body and is the largest organ. Skin cancer is one of the most dreadful
cancers that is primarily triggered by sensitivity to ultraviolet rays from the sun. However, the …
cancers that is primarily triggered by sensitivity to ultraviolet rays from the sun. However, the …
Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture
Brain tumor is one of the most dreadful natures of cancer and caused a huge number of
deaths among kids and adults from the past few years. According to WHO standard, the …
deaths among kids and adults from the past few years. According to WHO standard, the …
Brain tumor segmentation using K‐means clustering and deep learning with synthetic data augmentation for classification
Image processing plays a major role in neurologists' clinical diagnosis in the medical field.
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Several types of imagery are used for diagnostics, tumor segmentation, and classification …
Brain tumor detection and multi‐classification using advanced deep learning techniques
A brain tumor is an uncontrolled development of brain cells in brain cancer if not detected at
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
an early stage. Early brain tumor diagnosis plays a crucial role in treatment planning and …
Brain tumor segmentation using convolutional neural networks in MRI images
In medical image processing, Brain tumor segmentation plays an important role. Early
detection of these tumors is highly required to give Treatment of patients. The patient's life …
detection of these tumors is highly required to give Treatment of patients. The patient's life …
[PDF][PDF] Brain tumor detection using mri images and convolutional neural network
D Lamrani, B Cherradi, O El Gannour… - … Journal of Advanced …, 2022 - researchgate.net
A brain tumor is the cause of abnormal growth of cells in the brain. Magnetic resonance
imaging (MRI) is the most practical method for detecting brain tumors. Through these MRIs …
imaging (MRI) is the most practical method for detecting brain tumors. Through these MRIs …
Artificial intelligence in brain tumor detection through MRI scans: advancements and challenges
A brain tumor is one of the most perilous diseases in human beings. The manual
segmentation of brain tumors is costly and takes a lot of time; due to this reason, automated …
segmentation of brain tumors is costly and takes a lot of time; due to this reason, automated …
Hybrid segmentation method with confidence region detection for tumor identification
Segmentation methods can mutually exclude the location of the tumor. However, the
challenge of complex location or incomplete identification is located in segmentation …
challenge of complex location or incomplete identification is located in segmentation …
Brain tumor segmentation and classification in MRI using SVM and its variants: a survey
S Vadhnani, N Singh - Multimedia Tools and Applications, 2022 - Springer
The process of separation of brain tumor from normal brain tissues is Brain tumor
segmentation. Segmentation of tumor from the MR images is a very challenging task as …
segmentation. Segmentation of tumor from the MR images is a very challenging task as …