AIMC Topic: Image Interpretation, Computer-Assisted

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Optimised Hybrid Attention-Based Capsule Network Integrated Three-Pathway Network for Chronic Disease Detection in Retinal Images.

Journal of evaluation in clinical practice
BACKGROUND: Over the past 20 years, researchers have concentrated on generating retinal images as a means of detecting and classifying chronic diseases. Early diagnosis and treatment are essential to avoid chronic diseases. Manually grading retinal i...

Digital Pathology and Artificial Intelligence in Pediatric Pathology.

Surgical pathology clinics
Applications of artificial intelligence (AI) and machine learning (ML) are rapidly developing to support the diagnosis and classification of pathology specimens. These tools rely on digitization of pathology glass slides as whole slide images, allowi...

Implementing 100% quality control in a cervical cytology workflow using whole slide images and artificial intelligence provided by the Techcyte SureView™ System.

Cancer cytopathology
BACKGROUND: Recent advancements in digital pathology have extended into cytopathology. Laboratories screening cervical cytology specimens now choose between limited imaging options and traditional manual microscopy. The Techcyte SureView™ Cervical Cy...

Exploring interpretable echo analysis using self-supervised parcels.

Computers in biology and medicine
The application of AI for predicting critical heart failure endpoints using echocardiography is a promising avenue to improve patient care and treatment planning. However, fully supervised training of deep learning models in medical imaging requires ...

Improving skin lesion classification through saliency-guided loss functions.

Computers in biology and medicine
Deep learning has significantly advanced computer-aided diagnosis, particularly in skin lesion classification. However, achieving high classification performance and providing explainable model predictions remain challenging in medical imaging. To ta...

Efficient polyp detection algorithm based on deep learning.

Scandinavian journal of gastroenterology
OBJECTIVE: Colon polyp detection is crucial in reducing the incidence of colorectal cancer. However, due to the diverse morphology of colon polyps, their high similarity to surrounding tissues, and the difficulty of detecting small target polyps, fal...

Real-time brain tumour diagnoses using a novel lightweight deep learning model.

Computers in biology and medicine
Brain tumours continue to be a primary cause of worldwide death, highlighting the critical need for effective and accurate diagnostic tools. This article presents MK-YOLOv8, an innovative lightweight deep learning framework developed for the real-tim...

DeepValve: The first automatic detection pipeline for the mitral valve in Cardiac Magnetic Resonance imaging.

Computers in biology and medicine
Mitral valve (MV) assessment is key to diagnosing valvular disease and to addressing its serious downstream complications. Cardiac magnetic resonance (CMR) has become an essential diagnostic tool in MV disease, offering detailed views of the valve st...

CellOMaps: A compact representation for robust classification of lung adenocarcinoma growth patterns.

Computers in biology and medicine
Lung adenocarcinoma (LUAD) is a morphologically heterogeneous disease, characterized by five primary histological growth patterns. The classification of such patterns is crucial due to their direct relation to prognosis but the high subjectivity and ...