AIMC Topic: Tomography, X-Ray Computed

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Efficient Liver Segmentation from Computed Tomography Images Using Deep Learning.

Computational intelligence and neuroscience May 18, 2022
Segmentation of a liver in computed tomography (CT) images is an important step toward quantitative biomarkers for a computer-aided decision support system and precise medical diagnosis. To overcome the difficulties that come across the liver segment...
Liver Tomography, X-Ray Computed Deep Learning Machine Learning Algorithms
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Deep Learning Assessment of Emphysema Progression at CT Predicts Outcomes.

Radiology May 17, 2022
Pulmonary Emphysema Emphysema Humans Tomography, X-Ray Computed Deep Learning
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Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study.

Radiology May 17, 2022
Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is time consuming, is subjective, requires training, and is affected by variability that may limit sensitivity to longitudinal change. Purpose To evaluate t...
Humans Prospective Studies Female Aged Tomography, X-Ray Computed Deep Learning Middle Aged Pulmonary Emphysema Lung Pulmonary Disease, Chronic Obstructive Severity of Illness Index Male Emphysema
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Automatic contouring QA method using a deep learning-based autocontouring system.

Journal of applied clinical medical physics May 17, 2022
PURPOSE: To determine the most accurate similarity metric when using an independent system to verify automatically generated contours.
Algorithms Tomography, X-Ray Computed Humans Female Deep Learning Lymph Nodes Pelvis Radiotherapy Planning, Computer-Assisted
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Development of an anthropomorphic multimodality pelvic phantom for quantitative evaluation of a deep-learning-based synthetic computed tomography generation technique.

Journal of applied clinical medical physics May 17, 2022
PURPOSE: The objective of this study was to fabricate an anthropomorphic multimodality pelvic phantom to evaluate a deep-learning-based synthetic computed tomography (CT) algorithm for magnetic resonance (MR)-only radiotherapy.
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Phantoms, Imaging Magnetic Resonance Imaging Pelvis Male Deep Learning Humans Tomography, X-Ray Computed
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A Novel Deep Learning Network and Its Application for Pulmonary Nodule Segmentation.

Computational intelligence and neuroscience May 17, 2022
Pulmonary nodules are the early manifestation of lung cancer, which appear as circular shadow of no more than 3 cm on the computed tomography (CT) image. Accurate segmentation of the contours of pulmonary nodules can help doctors improve the efficien...
Multiple Pulmonary Nodules Humans Deep Learning Tomography, X-Ray Computed Lung Neoplasms
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Development of a deep learning-based auto-segmentation algorithm for hepatocellular carcinoma (HCC) and application to predict microvascular invasion of HCC using CT texture analysis: preliminary results.

Acta radiologica (Stockholm, Sweden : 1987) May 16, 2022
BACKGROUND: Automatic segmentation has recently been developed to yield objective data. Prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) using radiomics has been reported.
Algorithms Retrospective Studies Tomography, X-Ray Computed Humans Liver Neoplasms Carcinoma, Hepatocellular Reproducibility of Results Neoplasm Invasiveness Deep Learning
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Tackling the class imbalance problem of deep learning-based head and neck organ segmentation.

International journal of computer assisted radiology and surgery May 16, 2022
PURPOSE: The segmentation of organs at risk (OAR) is a required precondition for the cancer treatment with image- guided radiation therapy. The automation of the segmentation task is therefore of high clinical relevance. Deep learning (DL)-based medi...
Image Processing, Computer-Assisted Head and Neck Neoplasms Organs at Risk Tomography, X-Ray Computed Deep Learning Radiotherapy, Image-Guided Humans Neural Networks, Computer
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End-to-end deep learning for interior tomography with low-dose x-ray CT.

Physics in medicine and biology May 16, 2022
There are several x-ray computed tomography (CT) scanning strategies used to reduce radiation dose, such as (1) sparse-view CT, (2) low-dose CT and (3) region-of-interest (ROI) CT (called interior tomography). To further reduce the dose, sparse-view ...
Image Processing, Computer-Assisted Humans Artifacts Algorithms X-Rays Tomography, X-Ray Computed Deep Learning
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Special issue "The advance of solid tumor research in China": Prognosis prediction for stage II colorectal cancer by fusing computed tomography radiomics and deep-learning features of primary lesions and peripheral lymph nodes.

International journal of cancer May 13, 2022
Currently, the prognosis assessment of stage II colorectal cancer (CRC) remains a difficult clinical problem; therefore, more accurate prognostic predictors must be developed. In our study, we developed a prognostic prediction model for stage II CRC ...
Lymphatic Metastasis Deep Learning Lymph Nodes Humans Tomography, X-Ray Computed Retrospective Studies Prognosis Colorectal Neoplasms
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