U-net and its variants for medical image segmentation: A review of theory and applications
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …
tasks. These traits provide U-net with a high utility within the medical imaging community …
Image segmentation for MR brain tumor detection using machine learning: a review
Magnetic Resonance Imaging (MRI) has commonly been used to detect and diagnose brain
disease and monitor treatment as non-invasive imaging technology. MRI produces three …
disease and monitor treatment as non-invasive imaging technology. MRI produces three …
Brain tumor detection and classification using machine learning: a comprehensive survey
J Amin, M Sharif, A Haldorai, M Yasmin… - Complex & intelligent …, 2022 - Springer
Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
Medical image segmentation using deep learning: A survey
Deep learning has been widely used for medical image segmentation and a large number of
papers has been presented recording the success of deep learning in the field. A …
papers has been presented recording the success of deep learning in the field. A …
Multi-modal brain tumor detection using deep neural network and multiclass SVM
Background and Objectives: Clinical diagnosis has become very significant in today's health
system. The most serious disease and the leading cause of mortality globally is brain cancer …
system. The most serious disease and the leading cause of mortality globally is brain cancer …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
Deep learning for smart Healthcare—A survey on brain tumor detection from medical imaging
Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …
use of technology in medicine has made significant contributions to human society. In this …
Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation
The medical imaging literature has witnessed remarkable progress in high-performing
segmentation models based on convolutional neural networks. Despite the new …
segmentation models based on convolutional neural networks. Despite the new …
Deep learning for multigrade brain tumor classification in smart healthcare systems: A prospective survey
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade
recognition is a challenging problem for radiologists in health monitoring and automated …
recognition is a challenging problem for radiologists in health monitoring and automated …
A systematic review of artificial intelligence techniques in cancer prediction and diagnosis
Artificial intelligence has aided in the advancement of healthcare research. The availability
of open-source healthcare statistics has prompted researchers to create applications that aid …
of open-source healthcare statistics has prompted researchers to create applications that aid …