AIMC Topic: Diagnosis, Computer-Assisted

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Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach.

Computational and mathematical methods in medicine
Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important tasks for neurologists and radiologists is to detect brain tumors early. Recent claims have been made that computer-aided diagnosis-based systems can ...

Detection of mitotic HEp-2 cell images: role of feature representation and classification framework under class skew.

Medical & biological engineering & computing
We propose and analyze a framework to detect and identify the mitotic type staining patterns among different non-mitotic (interphase) patterns on HEp-2 cell substrate specimen images. This is considered as a principal task in computer-aided diagnosis...

Follow My Eye: Using Gaze to Supervise Computer-Aided Diagnosis.

IEEE transactions on medical imaging
When deep neural network (DNN) was first introduced to the medical image analysis community, researchers were impressed by its performance. However, it is evident now that a large number of manually labeled data is often a must to train a properly fu...

Hybrid Rider Optimization with Deep Learning Driven Biomedical Liver Cancer Detection and Classification.

Computational intelligence and neuroscience
Biomedical engineering is the application of the principles and problem-solving methods of engineering to biology along with medicine. Computation intelligence is the study of design of intelligent agents which are systems acting perceptively. The co...

Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies.

Digestion
INTRODUCTION: Computer-aided detection (CADe) helps increase colonoscopic polyp detection. However, little is known about other performance metrics like the number and duration of false-positive (FP) activations or how stable the detection of a polyp...

HunCRC: annotated pathological slides to enhance deep learning applications in colorectal cancer screening.

Scientific data
Histopathology is the gold standard method for staging and grading human tumors and provides critical information for the oncoteam's decision making. Highly-trained pathologists are needed for careful microscopic analysis of the slides produced from ...

Biomedical Microscopic Imaging in Computational Intelligence Using Deep Learning Ensemble Convolution Learning-Based Feature Extraction and Classification.

Computational intelligence and neuroscience
Microscopy image analysis gives quantitative support for enhancing the characterizations of various diseases, including breast cancer, lung cancer, and brain tumors. As a result, it is crucial in computer-assisted diagnosis and prognosis. Understandi...

Multisemantic Level Patch Merger Vision Transformer for Diagnosis of Pneumonia.

Computational and mathematical methods in medicine
The most popular test for pneumonia, a serious health threat to children, is chest X-ray imaging. However, the diagnosis of pneumonia relies on the expertise of experienced radiologists, and the scarcity of medical resources has forced us to conduct ...

Automatic Grading Assessments for Knee MRI Cartilage Defects via Self-ensembling Semi-supervised Learning with Dual-Consistency.

Medical image analysis
Knee cartilage defects caused by osteoarthritis are major musculoskeletal disorders, leading to joint necrosis or even disability if not intervened at early stage. Deep learning has demonstrated its effectiveness in computer-aided diagnosis, but it i...