AIMC Topic: Tomography, X-Ray Computed
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Clinically applicable semi-supervised learning framework for multiple organs at risk and tumor delineation in lung cancer brachytherapy.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Apr 1, 2025
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remains under-validated. We reported an investigation that validated a robust semi-supervised conditional ...
Semi-supervised spatial-frequency transformer for metal artifact reduction in maxillofacial CT and evaluation with intraoral scan.
European journal of radiology
Mar 31, 2025
PURPOSE: To develop a semi-supervised domain adaptation technique for metal artifact reduction with a spatial-frequency transformer (SFTrans) model (Semi-SFTrans), and to quantitatively compare its performance with supervised models (Sup-SFTrans and ...
An Early Thyroid Screening Model Based on Transformer and Secondary Transfer Learning for Chest and Thyroid CT Images.
Technology in cancer research & treatment
Mar 31, 2025
IntroductionThyroid cancer is a common malignant tumor, and early diagnosis and timely treatment are crucial to improve patient prognosis. With the increasing use of enhanced CT scans, a new opportunity for early thyroid cancer screening has emerged....
Exploring the Incremental Value of Aorta Enhancement Normalization Method in Evaluating Renal Cell Carcinoma Histological Subtypes: A Multi-center Large Cohort Study.
Academic radiology
Mar 28, 2025
RATIONALE AND OBJECTIVES: The classification of renal cell carcinoma (RCC) histological subtypes plays a crucial role in clinical diagnosis. However, traditional image normalization methods often struggle with discrepancies arising from differences i...
Artificial intelligence-based multimodal prediction for nuclear grading status and prognosis of clear cell renal cell carcinoma: a multicenter cohort study.
International journal of surgery (London, England)
Mar 28, 2025
BACKGROUND: The assessment of the International Society of Urological Pathology (ISUP) nuclear grade is crucial for the management and treatment of clear cell renal cell carcinoma (ccRCC). This study aimed to explore the value of using integrated mul...
ResTransUNet: A hybrid CNN-transformer approach for liver and tumor segmentation in CT images.
Computers in biology and medicine
Mar 28, 2025
BACKGROUND AND OBJECTIVE: Accurate medical tumor segmentation is critical for early diagnosis and treatment planning, significantly improving patient outcomes. This study aims to enhance liver and tumor segmentation from CT and liver images by develo...
A deep learning model for classification of chondroid tumors on CT images.
BMC cancer
Mar 28, 2025
BACKGROUND: Differentiating chondroid tumors is crucial for proper patient management. This study aimed to develop a deep learning model (DLM) for classifying enchondromas, atypical cartilaginous tumors (ACT), and high-grade chondrosarcomas using CT ...
Fine-tuned deep learning models for early detection and classification of kidney conditions in CT imaging.
Scientific reports
Mar 28, 2025
The kidney plays a vital role in maintaining homeostasis, but lifestyle factors and diseases can lead to kidney failures. Early detection of kidney disease is crucial for effective intervention, often challenging due to unnoticeable symptoms in the i...
Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy.
Technology in cancer research & treatment
Mar 28, 2025
The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90 selective internal radiation therapy (SIRT). A deep learning (DL)-based liver segmentation model using the U-Net3D architecture was built. Auto-segme...
LA-ResUNet: Attention-based network for longitudinal liver tumor segmentation from CT images.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 27, 2025
Longitudinal liver tumor segmentation plays a fundamental role in studying and monitoring the progression of associated diseases. The correlation and differences between longitudinal data can further improve segmentation performance, which are inevit...
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