AIMC Topic: Imaging, Three-Dimensional

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Self-supervised learning for classifying paranasal anomalies in the maxillary sinus.

International journal of computer assisted radiology and surgery Jun 8, 2024
PURPOSE: Paranasal anomalies, frequently identified in routine radiological screenings, exhibit diverse morphological characteristics. Due to the diversity of anomalies, supervised learning methods require large labelled dataset exhibiting diverse an...
Tomography, X-Ray Computed Imaging, Three-Dimensional Supervised Machine Learning Maxillary Sinus Humans Neural Networks, Computer
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Deep learning automatic semantic segmentation of glioblastoma multiforme regions on multimodal magnetic resonance images.

International journal of computer assisted radiology and surgery Jun 7, 2024
OBJECTIVES: In patients having naïve glioblastoma multiforme (GBM), this study aims to assess the efficacy of Deep Learning algorithms in automating the segmentation of brain magnetic resonance (MR) images to accurately determine 3D masks for 4 disti...
Humans Algorithms Semantics Magnetic Resonance Imaging Brain Neoplasms Multimodal Imaging Deep Learning Glioblastoma Imaging, Three-Dimensional
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Predicting Lymphovascular Invasion in Non-small Cell Lung Cancer Using Deep Convolutional Neural Networks on Preoperative Chest CT.

Academic radiology Jun 6, 2024
RATIONALE AND OBJECTIVES: Lymphovascular invasion (LVI) plays a significant role in precise treatments of non-small cell lung cancer (NSCLC). This study aims to build a non-invasive LVI prediction diagnosis model by combining preoperative CT images w...
Carcinoma, Non-Small-Cell Lung Lymphatic Metastasis Neoplasm Invasiveness Humans Predictive Value of Tests Deep Learning Neural Networks, Computer Imaging, Three-Dimensional Female Lung Neoplasms Aged Retrospective Studies Adult Tomography, X-Ray Computed Male Middle Aged
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MedYOLO: A Medical Image Object Detection Framework.

Journal of imaging informatics in medicine Jun 6, 2024
Artificial intelligence-enhanced identification of organs, lesions, and other structures in medical imaging is typically done using convolutional neural networks (CNNs) designed to make voxel-accurate segmentations of the region of interest. However,...
Imaging, Three-Dimensional Image Processing, Computer-Assisted Heart Artificial Intelligence Algorithms Tomography, X-Ray Computed Humans Neural Networks, Computer
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Volumetric analysis of acute uncomplicated type B aortic dissection using an automated deep learning aortic zone segmentation model.

Journal of vascular surgery Jun 6, 2024
BACKGROUND: Machine learning techniques have shown excellent performance in three-dimensional medical image analysis, but have not been applied to acute uncomplicated type B aortic dissection (auTBAD) using Society for Vascular Surgery (SVS) and Soci...
Aortography Middle Aged Aortic Aneurysm, Thoracic Computed Tomography Angiography Disease Progression Time Factors Humans Acute Disease Reproducibility of Results Imaging, Three-Dimensional Deep Learning Radiographic Image Interpretation, Computer-Assisted Aged Aortic Aneurysm Retrospective Studies Predictive Value of Tests Automation Male Female Aortic Dissection
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NKUT: Dataset and Benchmark for Pediatric Mandibular Wisdom Teeth Segmentation.

IEEE journal of biomedical and health informatics Jun 6, 2024
Germectomy is a common surgery in pediatric dentistry to prevent the potential dangers caused by impacted mandibular wisdom teeth. Segmentation of mandibular wisdom teeth is a crucial step in surgery planning. However, manually segmenting teeth and b...
Deep Learning Child Molar, Third Cone-Beam Computed Tomography Humans Algorithms Databases, Factual Datasets as Topic Imaging, Three-Dimensional Mandible Benchmarking
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Toward Ground-Truth Optical Coherence Tomography via Three-Dimensional Unsupervised Deep Learning Processing and Data.

IEEE transactions on medical imaging Jun 3, 2024
Optical coherence tomography (OCT) can perform non-invasive high-resolution three-dimensional (3D) imaging and has been widely used in biomedical fields, while it is inevitably affected by coherence speckle noise which degrades OCT imaging performanc...
Tomography, Optical Coherence Deep Learning Imaging, Three-Dimensional Humans Unsupervised Machine Learning
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MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3-D CT Lesions.

IEEE transactions on neural networks and learning systems Jun 3, 2024
With the renaissance of deep learning, automatic diagnostic algorithms for computed tomography (CT) have achieved many successful applications. However, they heavily rely on lesion-level annotations, which are often scarce due to the high cost of col...
Humans Neural Networks, Computer Deep Learning Imaging, Three-Dimensional Lung Neoplasms Unsupervised Machine Learning Algorithms Databases, Factual Tomography, X-Ray Computed
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Deep learning for 3D biliary anatomy for living liver donor hepatectomy planning.

International journal of surgery (London, England) Jun 1, 2024
Humans Biliary Tract Imaging, Three-Dimensional Deep Learning Liver Transplantation Liver Hepatectomy Living Donors
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Prediction of surgery-first approach orthognathic surgery using deep learning models.

International journal of oral and maxillofacial surgery May 31, 2024
The surgery-first approach (SFA) orthognathic surgery can be beneficial due to reduced overall treatment time and earlier profile improvement. The objective of this study was to utilize deep learning to predict the treatment modality of SFA or the or...
Orthognathic Surgical Procedures Deep Learning Humans Models, Dental Imaging, Three-Dimensional Malocclusion, Angle Class III Female Cephalometry Male
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