Cancer detection and segmentation using machine learning and deep learning techniques: A review
HM Rai - Multimedia Tools and Applications, 2024 - Springer
Cancer is the most fatal diseases in the world which has highest mortality rate as compared
to other type's human diseases. The most common and dangerous types of cancers are lung …
to other type's human diseases. The most common and dangerous types of cancers are lung …
Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm
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 …
of physicians and reduce the time required for accurate diagnosis. The objective of this …
Classification techniques in breast cancer diagnosis: a systematic literature review
Data mining (DM) consists in analysing a set of observations to find unsuspected
relationships and then summarising the data in new ways that are both understandable and …
relationships and then summarising the data in new ways that are both understandable and …
2D MRI image analysis and brain tumor detection using deep learning CNN model LeU-Net
MRI image analysis and its segmentation for the accurate and automatic detection of brain
tumors at an early stage is very much crucial for diagnosis the disorders and save human …
tumors at an early stage is very much crucial for diagnosis the disorders and save human …
Hybrid Tolerance Rough Set–Firefly based supervised feature selection for MRI brain tumor image classification
G Jothi - Applied Soft Computing, 2016 - Elsevier
Brain tumor is one of the most harmful diseases, and has affected majority of people
including children in the world. The probability of survival can be enhanced if the tumor is …
including children in the world. The probability of survival can be enhanced if the tumor is …
[HTML][HTML] Detection of brain abnormality by a novel Lu-Net deep neural CNN model from MR images
The identification and classification of tumors in the human mind from MR images at an early
stage play a pivotal role in diagnosis such diseases. This work presents the novel Deep …
stage play a pivotal role in diagnosis such diseases. This work presents the novel Deep …
Automatic and accurate abnormality detection from brain MR images using a novel hybrid UnetResNext-50 deep CNN model
The automatic and accurate detection and segmentation of brain tumors is a very tedious
and challenging task for medical experts and radiologists. This paper proposes a hybrid …
and challenging task for medical experts and radiologists. This paper proposes a hybrid …
Cancerous and non-cancerous brain MRI classification method based on convolutional neural network and log-polar transformation
Magnetic resonance imaging (MRI) offers visual representations of the interior of a body for
clinical analysis and medical intervention. The MRI process is subjected to a variety of …
clinical analysis and medical intervention. The MRI process is subjected to a variety of …
A two-stage feature selection approach for fruit recognition using camera images with various machine learning classifiers
Fruit and vegetable identification and classification system is always necessary and
advantageous for the agriculture business, the food processing sector, as well as the …
advantageous for the agriculture business, the food processing sector, as well as the …
[PDF][PDF] Computer-aided diagnosis of human brain tumor through MRI: A survey and a new algorithm
A El-Sayed, HM Mohsen, K Revett… - Expert systems with …, 2014 - academia.edu
abstract Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic
capabilities of physicians and reduce the time required for accurate diagnosis. The objective …
capabilities of physicians and reduce the time required for accurate diagnosis. The objective …