Brain tumor detection and classification using machine learning: a comprehensive survey
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 …
Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency
Abstract Despite that Convolutional Neural Networks (CNNs) have achieved promising
performance in many medical image segmentation tasks, they rely on a large set of labeled …
performance in many medical image segmentation tasks, they rely on a large set of labeled …
Semi-supervised medical image segmentation through dual-task consistency
Deep learning-based semi-supervised learning (SSL) algorithms have led to promising
results in medical images segmentation and can alleviate doctors' expensive annotations by …
results in medical images segmentation and can alleviate doctors' expensive annotations by …
AI in medical imaging informatics: current challenges and future directions
This paper reviews state-of-the-art research solutions across the spectrum of medical
imaging informatics, discusses clinical translation, and provides future directions for …
imaging informatics, discusses clinical translation, and provides future directions for …
Modality specific U-Net variants for biomedical image segmentation: a survey
With the advent of advancements in deep learning approaches, such as deep convolution
neural network, residual neural network, adversarial network; U-Net architectures are most …
neural network, residual neural network, adversarial network; U-Net architectures are most …
A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches
With the development of Computer-aided Diagnosis (CAD) and image scanning techniques,
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Chest X-ray pneumothorax segmentation using U-Net with EfficientNet and ResNet architectures
Medical imaging refers to visualization techniques to provide valuable information about the
internal structures of the human body for clinical applications, diagnosis, treatment, and …
internal structures of the human body for clinical applications, diagnosis, treatment, and …
MIDeepSeg: Minimally interactive segmentation of unseen objects from medical images using deep learning
Segmentation of organs or lesions from medical images plays an essential role in many
clinical applications such as diagnosis and treatment planning. Though Convolutional …
clinical applications such as diagnosis and treatment planning. Though Convolutional …
Skin lesion analysis and cancer detection based on machine/deep learning techniques: A comprehensive survey
The skin is the human body's largest organ and its cancer is considered among the most
dangerous kinds of cancer. Various pathological variations in the human body can cause …
dangerous kinds of cancer. Various pathological variations in the human body can cause …