AIMC Topic: Tomography, X-Ray Computed

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Enhancing fracture diagnosis in pelvic X-rays by deep convolutional neural network with synthesized images from 3D-CT.

Scientific reports Apr 5, 2024
Pelvic fractures pose significant challenges in medical diagnosis due to the complex structure of the pelvic bones. Timely diagnosis of pelvic fractures is critical to reduce complications and mortality rates. While computed tomography (CT) is highly...
Fractures, Bone Radiography X-Rays Humans Neural Networks, Computer Tomography, X-Ray Computed
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Application value of the automated machine learning model based on modified CT index combined with serological indices in the early prediction of lung cancer.

Frontiers in public health Apr 5, 2024
BACKGROUND AND OBJECTIVE: Accurately predicting the extent of lung tumor infiltration is crucial for improving patient survival and cure rates. This study aims to evaluate the application value of an improved CT index combined with serum biomarkers, ...
Female ROC Curve Algorithms Biomarkers, Tumor Humans Lung Neoplasms Retrospective Studies Male Aged Machine Learning Early Detection of Cancer Tomography, X-Ray Computed Middle Aged Adult
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Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning.

International journal of computer assisted radiology and surgery Apr 4, 2024
PURPOSE: Three-dimensional (3D) preoperative planning has become the gold standard for orthopedic surgeries, primarily relying on CT-reconstructed 3D models. However, in contrast to standing radiographs, a CT scan is not part of the standard protocol...
Humans Tibia Tomography, X-Ray Computed Preoperative Care Female Deep Learning Adult Imaging, Three-Dimensional Male Osteotomy Middle Aged
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Are deep learning classification results obtained on CT scans fair and interpretable?

Physical and engineering sciences in medicine Apr 4, 2024
Following the great success of various deep learning methods in image and object classification, the biomedical image processing society is also overwhelmed with their applications to various automatic diagnosis cases. Unfortunately, most of the deep...
Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Humans
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Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Apr 4, 2024
BACKGROUND: Pneumonitis is a well-described, potentially disabling, or fatal adverse effect associated with both immune checkpoint inhibitors (ICI) and thoracic radiotherapy. Accurate differentiation between checkpoint inhibitor pneumonitis (CIP) rad...
Middle Aged Humans Immune Checkpoint Inhibitors SARS-CoV-2 COVID-19 Machine Learning Lung Neoplasms Aged Tomography, X-Ray Computed Diagnosis, Differential Male Female Pneumonia Radiation Pneumonitis
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Registration of multimodal bone images based on edge similarity metaheuristic.

Computers in biology and medicine Apr 4, 2024
OBJECTIVE: Blurry medical images affect the accuracy and efficiency of multimodal image registration, whose existing methods require further improvement.
Humans Neural Networks, Computer Bone and Bones Tomography, X-Ray Computed Algorithms Image Processing, Computer-Assisted Multimodal Imaging
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Deep Learning for Automated Measurement of Total Cardiac Volume for Heart Transplantation Size Matching.

Pediatric cardiology Apr 3, 2024
Total Cardiac Volume (TCV)-based size matching using Computed Tomography (CT) is a novel technique to compare donor and recipient heart size in pediatric heart transplant that may increase overall utilization of available grafts. TCV requires manual ...
Infant, Newborn Young Adult Adult Retrospective Studies Tomography, X-Ray Computed Female Adolescent Child, Preschool Child Male Infant Deep Learning Humans Neural Networks, Computer Heart Transplantation Cardiac Volume Imaging, Three-Dimensional Organ Size Heart
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Estimate and compensate head motion in non-contrast head CT scans using partial angle reconstruction and deep learning.

Medical physics Apr 3, 2024
BACKGROUND: Patient head motion is a common source of image artifacts in computed tomography (CT) of the head, leading to degraded image quality and potentially incorrect diagnoses. The partial angle reconstruction (PAR) means dividing the CT project...
Tomography, X-Ray Computed Head Movements Humans Deep Learning Artifacts Image Processing, Computer-Assisted Head Phantoms, Imaging
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Hierarchical decomposed dual-domain deep learning for sparse-view CT reconstruction.

Physics in medicine and biology Apr 3, 2024
. X-ray computed tomography employing sparse projection views has emerged as a contemporary technique to mitigate radiation dose. However, due to the inadequate number of projection views, an analytic reconstruction method utilizing filtered backproj...
Deep Learning Phantoms, Imaging Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted Artifacts
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SC-SSL: Self-Correcting Collaborative and Contrastive Co-Training Model for Semi-Supervised Medical Image Segmentation.

IEEE transactions on medical imaging Apr 3, 2024
Image segmentation achieves significant improvements with deep neural networks at the premise of a large scale of labeled training data, which is laborious to assure in medical image tasks. Recently, semi-supervised learning (SSL) has shown great pot...
Image Processing, Computer-Assisted Supervised Machine Learning Semantics Neural Networks, Computer Tomography, X-Ray Computed
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