AIMC Topic: Image Interpretation, Computer-Assisted
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Liver Cancer Diagnosis: Enhanced Deep Maxout Model with Improved Feature Set.
Cancer investigation
Aug 27, 2024
This work proposed a liver cancer classification scheme that includes Preprocessing, Feature extraction, and classification stages. The source images are pre-processed using Gaussian filtering. For segmentation, this work proposes a LUV transformatio...
Artificial intelligence for retinal diseases.
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Aug 27, 2024
PURPOSE: To discuss the worldwide applications and potential impact of artificial intelligence (AI) for the diagnosis, management and analysis of treatment outcomes of common retinal diseases.
US-based Radiomics Analysis of Different Machine Learning Models for Differentiating Benign and Malignant BI-RADS 4A Breast Lesions.
Academic radiology
Aug 26, 2024
RATIONALE AND OBJECTIVES: To investigate and authenticate the effectiveness of various radiomics models in distinguishing between benign and malignant BI-RADS 4A lesions.
Radiomic and deep learning analysis of dermoscopic images for skin lesion pattern decoding.
Scientific reports
Aug 26, 2024
This study aims to explore the efficacy of a hybrid deep learning and radiomics approach, supplemented with patient metadata, in the noninvasive dermoscopic imaging-based diagnosis of skin lesions. We analyzed dermoscopic images from the Internationa...
Computerizing the first step of the two-step algorithm in dermoscopy: A convolutional neural network for differentiating melanocytic from non-melanocytic skin lesions.
European journal of cancer (Oxford, England : 1990)
Aug 25, 2024
IMPORTANCE: Convolutional neural networks (CNN) have shown performance equal to trained dermatologists in differentiating benign from malignant skin lesions. To improve clinicians' management decisions, additional classifications into diagnostic cate...
Accuracy of vestibular schwannoma segmentation using deep learning models - a systematic review & meta-analysis.
Neuroradiology
Aug 24, 2024
UNLABELLED: Vestibular Schwannoma (VS) is a rare tumor with varied incidence rates, predominantly affecting the 60-69 age group. In the era of artificial intelligence (AI), deep learning (DL) algorithms show promise in automating diagnosis. However, ...
Artificial intelligence-assisted volume isotropic simultaneous interleaved bright- and black-blood examination for brain metastases.
Neuroradiology
Aug 22, 2024
PURPOSE: To verify the effectiveness of artificial intelligence-assisted volume isotropic simultaneous interleaved bright-/black-blood examination (AI-VISIBLE) for detecting brain metastases.
Skeleton-guided multi-scale dual-coordinate attention aggregation network for retinal blood vessel segmentation.
Computers in biology and medicine
Aug 22, 2024
Deep learning plays a pivotal role in retinal blood vessel segmentation for medical diagnosis. Despite their significant efficacy, these techniques face two major challenges. Firstly, they often neglect the severe class imbalance in fundus images, wh...
Beyond the Conventional Structural MRI: Clinical Application of Deep Learning Image Reconstruction and Synthetic MRI of the Brain.
Investigative radiology
Aug 20, 2024
Recent technological advancements have revolutionized routine brain magnetic resonance imaging (MRI) sequences, offering enhanced diagnostic capabilities in intracranial disease evaluation. This review explores 2 pivotal breakthrough areas: deep lear...
An Unsupervised Learning Tool for Plaque Tissue Characterization in Histopathological Images.
Sensors (Basel, Switzerland)
Aug 20, 2024
Stroke is the second leading cause of death and a major cause of disability around the world, and the development of atherosclerotic plaques in the carotid arteries is generally considered the leading cause of severe cerebrovascular events. In recent...
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