AIMC Topic: Tomography, X-Ray Computed

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Enhancing trabecular CT scans based on deep learning with multi-strategy fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jun 12, 2024
Trabecular bone analysis plays a crucial role in understanding bone health and disease, with applications like osteoporosis diagnosis. This paper presents a comprehensive study on 3D trabecular computed tomography (CT) image restoration, addressing s...
Humans Tomography, X-Ray Computed Deep Learning Imaging, Three-Dimensional Cancellous Bone
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Image-domain material decomposition for dual-energy CT using unsupervised learning with data-fidelity loss.

Medical physics Jun 12, 2024
BACKGROUND: Dual-energy computed tomography (DECT) and material decomposition play vital roles in quantitative medical imaging. However, the decomposition process may suffer from significant noise amplification, leading to severely degraded image sig...
Image Processing, Computer-Assisted Unsupervised Machine Learning Signal-To-Noise Ratio Tomography, X-Ray Computed Deep Learning Humans
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Machine learning for predicting hematoma expansion in spontaneous intracerebral hemorrhage: a systematic review and meta-analysis.

Neuroradiology Jun 12, 2024
PURPOSE: Early identification of hematoma enlargement and persistent hematoma expansion (HE) in patients with cerebral hemorrhage is increasingly crucial for determining clinical treatments. However, due to the lack of clinically effective tools, rad...
Cerebral Hemorrhage Predictive Value of Tests Hematoma Machine Learning Tomography, X-Ray Computed Disease Progression Humans
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FasterRib: A deep learning algorithm to automate identification and characterization of rib fractures on chest computed tomography scans: Erratum.

The journal of trauma and acute care surgery Jun 12, 2024
Rib Fractures Humans Tomography, X-Ray Computed Algorithms Deep Learning
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Histological Subtype Classification of Non-Small Cell Lung Cancer with Radiomics and 3D Convolutional Neural Networks.

Journal of imaging informatics in medicine Jun 11, 2024
Non-small cell lung carcinoma (NSCLC) is the most common type of pulmonary cancer, one of the deadliest malignant tumors worldwide. Given the increased emphasis on the precise management of lung cancer, identifying various subtypes of NSCLC has becom...
Tomography, X-Ray Computed Radiomics Deep Learning Humans Neural Networks, Computer Carcinoma, Non-Small-Cell Lung Imaging, Three-Dimensional Lung Neoplasms
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Res-TransNet: A Hybrid deep Learning Network for Predicting Pathological Subtypes of lung Adenocarcinoma in CT Images.

Journal of imaging informatics in medicine Jun 11, 2024
This study aims to develop a CT-based hybrid deep learning network to predict pathological subtypes of early-stage lung adenocarcinoma by integrating residual network (ResNet) with Vision Transformer (ViT). A total of 1411 pathologically confirmed gr...
Image Processing, Computer-Assisted Lung Neoplasms Adenocarcinoma of Lung Retrospective Studies Tomography, X-Ray Computed Male Female Humans Middle Aged Computer Simulation Deep Learning
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Deep learning-based correction for time truncation in cerebral computed tomography perfusion.

Radiological physics and technology Jun 11, 2024
Cerebral computed tomography perfusion (CTP) imaging requires complete acquisition of contrast bolus inflow and washout in the brain parenchyma; however, time truncation undoubtedly occurs in clinical practice. To overcome this issue, we proposed a t...
Deep Learning Time Factors Image Processing, Computer-Assisted Female Male Perfusion Imaging Humans Brain Tomography, X-Ray Computed
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Deep learning model utilizing clinical data alone outperforms image-based model for hernia recurrence following abdominal wall reconstruction with long-term follow up.

Surgical endoscopy Jun 11, 2024
BACKGROUND: Deep learning models (DLMs) using preoperative computed tomography (CT) imaging have shown promise in predicting outcomes following abdominal wall reconstruction (AWR), including component separation, wound complications, and pulmonary fa...
Humans Abdominal Wall Middle Aged Deep Learning Aged Retrospective Studies Recurrence Follow-Up Studies Adult Tomography, X-Ray Computed Herniorrhaphy Female Male Hernia, Ventral
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Artificial intelligence-driven computer aided diagnosis system provides similar diagnosis value compared with doctors' evaluation in lung cancer screening.

BMC medical imaging Jun 11, 2024
OBJECTIVE: To evaluate the consistency between doctors and artificial intelligence (AI) software in analysing and diagnosing pulmonary nodules, and assess whether the characteristics of pulmonary nodules derived from the two methods are consistent fo...
Diagnosis, Computer-Assisted ROC Curve Lung Neoplasms Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Adult Male Middle Aged Female Aged Software Retrospective Studies Tomography, X-Ray Computed Humans Neural Networks, Computer Artificial Intelligence
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Contrastive Learning vs. Self-Learning vs. Deformable Data Augmentation in Semantic Segmentation of Medical Images.

Journal of imaging informatics in medicine Jun 10, 2024
To develop a robust segmentation model, encoding the underlying features/structures of the input data is essential to discriminate the target structure from the background. To enrich the extracted feature maps, contrastive learning and self-learning ...
Humans Magnetic Resonance Imaging Tomography, X-Ray Computed Hippocampus Deep Learning Semantics Brain Neoplasms Image Processing, Computer-Assisted Kidney
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