Deep learning for medical anomaly detection–a survey
Machine learning–based medical anomaly detection is an important problem that has been
extensively studied. Numerous approaches have been proposed across various medical …
extensively studied. Numerous approaches have been proposed across various medical …
[HTML][HTML] The impact of pre-and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning
We address the challenging problem of whole slide image (WSI) classification. WSIs have
very high resolutions and usually lack localized annotations. WSI classification can be cast …
very high resolutions and usually lack localized annotations. WSI classification can be cast …
A review of deep learning on medical image analysis
Compared with common deep learning methods (eg, convolutional neural networks),
transfer learning is characterized by simplicity, efficiency and its low training cost, breaking …
transfer learning is characterized by simplicity, efficiency and its low training cost, breaking …
Pneumonia detection in chest X-ray images using convolutional neural networks and transfer learning
A large number of children die due to pneumonia every year worldwide. An estimated 1.2
million episodes of pneumonia were reported in children up to 5 years of age, of which …
million episodes of pneumonia were reported in children up to 5 years of age, of which …
An enhanced deep learning approach for brain cancer MRI images classification using residual networks
Cancer is the second leading cause of death after cardiovascular diseases. Out of all types
of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types …
of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types …
[HTML][HTML] Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained
images of TCGA samples remain underutilized. To highlight this resource, we present …
images of TCGA samples remain underutilized. To highlight this resource, we present …
Weakly supervised deep learning for whole slide lung cancer image analysis
Histopathology image analysis serves as the gold standard for cancer diagnosis. Efficient
and precise diagnosis is quite critical for the subsequent therapeutic treatment of patients …
and precise diagnosis is quite critical for the subsequent therapeutic treatment of patients …
Brain tumor detection and classification using intelligence techniques: an overview
S Solanki, UP Singh, SS Chouhan, S Jain - IEEE Access, 2023 - ieeexplore.ieee.org
A tumor is carried on by rapid and uncontrolled cell growth in the brain. If it is not treated in
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …
A deep feature learning model for pneumonia detection applying a combination of mRMR feature selection and machine learning models
Pneumonia is one of the diseases that people may encounter in any period of their lives.
Approximately 18% of infectious diseases are caused by pneumonia. This disease may …
Approximately 18% of infectious diseases are caused by pneumonia. This disease may …