AIMC Topic: Image Processing, Computer-Assisted

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AI-powered SPOT imaging for enhanced myocardial scar detection and quantification.

Nature communications
Cardiovascular disease is the leading global cause of death, underscoring the need for accurate assessment of myocardial injury. The current gold standard, bright-blood late gadolinium enhanced MRI, suffers from poor contrast at the blood-scar interf...

Polychromatic neural CBCT reconstruction through density-attenuation modeling.

Physics in medicine and biology
Monochromatic cone beam computed tomography reconstruction algorithms are still most prominent in practice. Since the x-ray detectors of today's machines are mostly energy integrating detectors and thus not able to resolve photon energy levels, recon...

New biomarkers to predict the need for surgery of necrotizing enterocolitis: a study based on abdominal X-ray radiomics and machine learning.

Biomedical engineering online
BACKGROUND: Necrotizing enterocolitis (NEC) is an inflammatory intestinal disease that primarily affects premature infants and is a major cause of death in the neonatal period. Approximately half of the affected infants require surgical intervention,...

RAUM-GANs: a multi-layer GAN-enhanced framework for accurate multiple sclerosis lesion segmentation in MRI.

Scientific reports
Multiple sclerosis (MS) is a chronic autoimmune disease characterized by inflammatory brain lesions, making MRI-based lesion segmentation challenging due to noise, missing data, and limited availability of high-quality labeled images. This paper pres...

Image Generation of Common Dermatological Diagnoses by Artificial Intelligence: Evaluation Study of the Potential for Education and Training Purposes.

JMIR dermatology
BACKGROUND: The integration of artificial intelligence (AI) into dermatology holds promise for education and diagnostic purposes, particularly through image generation, which has not been well studied.

Dynamic kernel generation through hybrid involution and convolution neural networks for leukemia and white blood cell classification.

Scientific reports
Blood cancer diagnosis through microscopic image analysis is challenging due to subtle morphological differences between cell stages and subtypes. This study aims to develop a Hybrid Involutional-Convolutional Neural Network (HICNN) for automated leu...

seg2med: a bridge from artificial anatomy to multimodal medical images.

Physics in medicine and biology
. We present seg2med (segmentation-to-medical images), a modular framework for anatomy-driven multimodal medical image synthesis. The system integrates three components to enable high-fidelity, cross-modality generation of computed tomography (CT) an...

PRCnet: An efficient model for automatic detection of brain tumor in MRI images.

PloS one
Brain tumors are the most prevalent and life-threatening cancer; an early and accurate diagnosis of brain tumors increases the chances of patient survival and treatment planning. However, manual tumor detection is a complex, cumbersome and time-consu...

Segmentation of plateau zokor mounds in alpine meadows from UAV images using an improved UNet network.

Scientific reports
Plateau zokor mounds, created by the burrowing activity of Plateau zokor, cause significant damage to crops, grasslands, and infrastructure, particularly in the alpine meadows of the Tibetan Plateau. Traditional field surveys are inefficient and labo...

An intelligent framework for visually impaired people through indoor object Detection-Based assistive system using YOLO with recurrent neural networks.

Scientific reports
Vision is a fundamental sense that profoundly impacts daily life and independence. For visually impaired people (VIP), the absence or impairment of this sense presents significant challenges, particularly in navigating their environment and identifyi...