AIMC Topic: Tomography, X-Ray Computed
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MetaGP: A generative foundation model integrating electronic health records and multimodal imaging for addressing unmet clinical needs.
Cell reports. Medicine
Apr 4, 2025
Artificial intelligence makes strides in specialized diagnostics but faces challenges in complex clinical scenarios, such as rare disease diagnosis and emergency condition identification. To address these limitations, we develop Meta General Practiti...
Feature Separation in Diffuse Lung Disease Image Classification by Using Evolutionary Algorithm-Based NAS.
IEEE journal of biomedical and health informatics
Apr 4, 2025
In the field of diagnosing lung diseases, the application of neural networks (NNs) in image classification exhibits significant potential. However, NNs are considered "black boxes," making it difficult to discern their decision-making processes, ther...
Radiomics across modalities: a comprehensive review of neurodegenerative diseases.
Clinical radiology
Apr 3, 2025
Radiomics allows extraction from medical images of quantitative features that are able to reveal tissue patterns that are generally invisible to human observers. Despite the challenges in visually interpreting radiomic features and the computational ...
A Neural Network Model for Intelligent Classification of Distal Radius Fractures Using Statistical Shape Model Extraction Features.
Orthopaedic surgery
Apr 3, 2025
OBJECTIVE: Distal radius fractures account for 12%-17% of all fractures, with accurate classification being crucial for proper treatment planning. Studies have shown that in emergency settings, the misdiagnosis rate of hand/wrist fractures can reach ...
Large Language Models in Summarizing Radiology Report Impressions for Lung Cancer in Chinese: Evaluation Study.
Journal of medical Internet research
Apr 3, 2025
BACKGROUND: Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various natural language processing tasks, particularly in text generation. However, their effectiveness in summarizing radiology report impressio...
Tackling Modality-Heterogeneous Client Drift Holistically for Heterogeneous Multimodal Federated Learning.
IEEE transactions on medical imaging
Apr 3, 2025
Multimodal Federated Learning (MFL) has emerged as a collaborative paradigm for training models across decentralized devices, harnessing various data modalities to facilitate effective learning while respecting data ownership. In this realm, notably,...
Improved unsupervised 3D lung lesion detection and localization by fusing global and local features: Validation in 3D low-dose computed tomography.
Medical image analysis
Apr 1, 2025
Unsupervised anomaly detection (UAD) is crucial in low-dose computed tomography (LDCT). Recent AI technologies, leveraging global features, have enabled effective UAD with minimal training data of normal patients. However, this approach, devoid of ut...
Trade-off of different deep learning-based auto-segmentation approaches for treatment planning of pediatric craniospinal irradiation autocontouring of OARs for pediatric CSI.
Medical physics
Apr 1, 2025
BACKGROUND: As auto-segmentation tools become integral to radiotherapy, more commercial products emerge. However, they may not always suit our needs. One notable example is the use of adult-trained commercial software for the contouring of organs at ...
Uncertainty quantification for CT dosimetry based on 10 281 subjects using automatic image segmentation and fast Monte Carlo calculations.
Medical physics
Apr 1, 2025
BACKGROUND: Computed tomography (CT) scans are a major source of medical radiation exposure worldwide. In countries like China, the frequency of CT scans has grown rapidly, thus making available a large volume of organ dose information. With modern c...
A CNN-transformer fusion network for predicting high-grade patterns in stage IA invasive lung adenocarcinoma.
Medical physics
Apr 1, 2025
BACKGROUND: Invasive lung adenocarcinoma (LUAD) with the high-grade patterns (HGPs) has the potential for rapid metastasis and frequent recurrence. Therefore, accurately predicting the presence of high-grade components is crucial for doctors to devel...
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