AIMC Topic: Image Interpretation, Computer-Assisted

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Evaluating Undersampling Schemes and Deep Learning Reconstructions for High-Resolution 3D Double Echo Steady State Knee Imaging at 7 T: A Comparison Between GRAPPA, CAIPIRINHA, and Compressed Sensing.

Investigative radiology
OBJECTIVE: The 3-dimensional (3D) double echo steady state (DESS) magnetic resonance imaging sequence can image knee cartilage with high, isotropic resolution, particularly at high and ultra-high field strengths. Advanced undersampling techniques wit...

Multimodal feature distinguishing and deep learning approach to detect lung disease from MRI images.

Scientific reports
Precise and early detection and diagnosis of lung diseases reduce the severity of life risk and further spread of infections in patients. Computer-based image processing techniques utilize magnetic resonance imaging (MRI) as input for computing, dete...

MV2SwimNet: A lightweight transformer-based hybrid model for knee meniscus tears detection.

PloS one
Knee Ailments, such as meniscus injuries, bother millions globally, with research showing that more than 14% of the population above 40 years lives with meniscus-related conditions. Conventional diagnosis techniques, like manual MRI interpretation, a...

Optimized deep learning for brain tumor detection: a hybrid approach with attention mechanisms and clinical explainability.

Scientific reports
Brain tumor classification (BTC) from Magnetic Resonance Imaging (MRI) is a critical diagnosis task, which is highly important for treatment planning. In this study, we propose a hybrid deep learning (DL) model that integrates VGG16, an attention mec...

AlzFormer: Multi-modal framework for Alzheimer's classification using MRI and graph-embedded demographics guided by adaptive attention gating.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Alzheimer's disease (AD) is the most common neurodegenerative progressive disorder and the fifth-leading cause of death in older people. The detection of AD is a very challenging task for clinicians and radiologists due to the complex nature of this ...

Enhancing cardiac function assessment: Developing and validating a domain adaptive framework for automating the segmentation of echocardiogram videos.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: Accurate segmentation of echocardiographic images is essential for assessing cardiac function, particularly in calculating key metrics such as ejection fraction. However, challenges such as domain discrepancy, noisy data, anatomical varia...

Multimodal data fusion with irregular PSA kinetics for automated prostate cancer grading.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Prostate cancer (PCa) detection and accurate grading remain critical challenges in medical diagnostics. While deep learning has shown promise in medical image analysis, existing computer-aided diagnosis approaches primarily focus on image recognition...

Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis.

Scientific reports
Recent innovations in medical imaging have markedly improved brain tumor identification, surpassing conventional diagnostic approaches that suffer from low resolution, radiation exposure, and limited contrast. Magnetic Resonance Imaging (MRI) is pivo...

BCDCNN: breast cancer deep convolutional neural network for breast cancer detection using MRI images.

Scientific reports
Breast cancer (BC) is a kind of cancer that is created from the cells in breast tissue. This is a primary cancer that occurs in women. Earlier identification of BC is significant in the treatment process. To lessen unwanted biopsies, Magnetic Resonan...

Multi-module UNet++ for colon cancer histopathological image segmentation.

Scientific reports
In the pathological diagnosis of colorectal cancer, the precise segmentation of glandular and cellular contours serves as the fundamental basis for achieving accurate clinical diagnosis. However, this task presents significant challenges due to compl...