AIMC Topic: Deep Learning

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A novel deep learning model for a computed tomography diagnosis of coronary plaque erosion.

Scientific reports
Patients with acute coronary syndromes caused by plaque erosion might be managed conservatively without stenting. Currently, the diagnosis of plaque erosion requires an invasive imaging procedure. We sought to develop a deep learning (DL) model that ...

Exploring the infiltrative and degradative ability of Fusarium oxysporum on polyethylene terephthalate (PET) using correlative microscopy and deep learning.

Scientific reports
Managing the worldwide steady increase in the production of plastic while mitigating the Earth's global pollution is one of the greatest challenges nowadays. Fungi are often involved in biodegradation processes thanks to their ability to penetrate in...

CRPU-NET: a deep learning model based semantic segmentation for the detection of colorectal polyp in lower gastrointestinal tract.

Biomedical physics & engineering express
. The objectives of the proposed work are twofold. Firstly, to develop a specialized light weight CRPU-Net for the segmentation of polyps in colonoscopy images. Secondly, to conduct a comparative analysis of the performance of CRPU-Net with implement...

Crowdsourcing image segmentation for deep learning: integrated platform for citizen science, paid microtask, and gamification.

Biomedizinische Technik. Biomedical engineering
OBJECTIVES: Segmentation is crucial in medical imaging. Deep learning based on convolutional neural networks showed promising results. However, the absence of large-scale datasets and a high degree of inter- and intra-observer variations pose a bottl...

Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification.

Molecular & cellular proteomics : MCP
Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with this technology is the relatively low rate of phosphopeptide identification during data analysis. This ...

Combining physical mechanisms and deep learning models for hourly surface ozone retrieval in China.

Journal of environmental management
As surface ozone (O) gains increasing attention, there is an urgent need for high temporal resolution and accurate O monitoring. By taking advantage of the progress in artificial intelligence, deep learning models have been applied to satellite based...

Understanding Naturalistic Facial Expressions with Deep Learning and Multimodal Large Language Models.

Sensors (Basel, Switzerland)
This paper provides a comprehensive overview of affective computing systems for facial expression recognition (FER) research in naturalistic contexts. The first section presents an updated account of user-friendly FER toolboxes incorporating state-of...

Super-resolution dual-layer CBCT imaging with model-guided deep learning.

Physics in medicine and biology
This study aims at investigating a novel super resolution CBCT imaging approach with a dual-layer flat panel detector (DL-FPD).With DL-FPD, the low-energy and high-energy projections acquired from the top and bottom detector layers contain over-sampl...

Machine and Deep Learning Dominate Recent Innovations in Sensors, Signals and Imaging Informatics.

Yearbook of medical informatics
OBJECTIVES: This review presents research papers highlighting notable developments and trends in sensors, signals, and imaging informatics (SSII) in 2022.