AIMC Topic: Imaging, Three-Dimensional

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CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.

Medical image analysis Mar 21, 2019
Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is a crucial step for radiation therapy in the treatment of prostate cancer. However, it is a very challenging task due to unclear boundaries, large intr...
Radiographic Image Interpretation, Computer-Assisted Organs at Risk Urinary Bladder Imaging, Three-Dimensional Prostatic Neoplasms Rectum Male Deep Learning Humans Tomography, X-Ray Computed
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Deep convolutional neural network for segmentation of thoracic organs-at-risk using cropped 3D images.

Medical physics Mar 21, 2019
PURPOSE: Automatic segmentation of organs-at-risk (OARs) is a key step in radiation treatment planning to reduce human efforts and bias. Deep convolutional neural networks (DCNN) have shown great success in many medical image segmentation application...
Imaging, Three-Dimensional Organs at Risk Thorax Radiotherapy, Image-Guided Neural Networks, Computer Tomography, X-Ray Computed
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Incorporating prior knowledge via volumetric deep residual network to optimize the reconstruction of sparsely sampled MRI.

Magnetic resonance imaging Mar 14, 2019
For sparse sampling that accelerates magnetic resonance (MR) image acquisition, non-linear reconstruction algorithms have been developed, which incorporated patient specific a prior information. More generic a prior information could be acquired via ...
Artifacts Cartilage Humans Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Magnetic Resonance Imaging Retrospective Studies Imaging, Three-Dimensional
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Automatic segmentation of bone surfaces from ultrasound using a filter-layer-guided CNN.

International journal of computer assisted radiology and surgery Mar 13, 2019
PURPOSE: Ultrasound (US) provides real-time, two-/three-dimensional safe imaging. Due to these capabilities, it is considered a safe alternative to intra-operative fluoroscopy in various computer-assisted orthopedic surgery (CAOS) procedures. However...
Neural Networks, Computer Ultrasonography Imaging, Three-Dimensional Surgery, Computer-Assisted Humans Bone and Bones Orthopedic Procedures
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Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models.

PloS one Mar 13, 2019
The health and function of tissue rely on its vasculature network to provide reliable blood perfusion. Volumetric imaging approaches, such as multiphoton microscopy, are able to generate detailed 3D images of blood vessels that could contribute to ou...
Imaging, Three-Dimensional Alzheimer Disease Humans Mice Cerebral Cortex Cerebral Angiography Neural Networks, Computer Disease Models, Animal Mice, Transgenic Microscopy, Fluorescence, Multiphoton Animals
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Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach.

International journal of computer assisted radiology and surgery Mar 7, 2019
PURPOSE: In radiation therapy, a key step for a successful cancer treatment is image-based treatment planning. One objective of the planning phase is the fast and accurate segmentation of organs at risk and target structures from medical images. Howe...
Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Imaging, Three-Dimensional Humans Head and Neck Neoplasms Observer Variation
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Feasibility of support vector machine learning in age-related macular degeneration using small sample yielding sparse optical coherence tomography data.

Acta ophthalmologica Mar 6, 2019
PURPOSE: A retrospective pilot study is conducted to demonstrate the utility of a novel support vector machine learning (SVML) algorithm in a small three-dimensional (3D) sample yielding sparse optical coherence tomography (spOCT) data for the automa...
Follow-Up Studies Aged Tomography, Optical Coherence Aged, 80 and over Male Feasibility Studies Pilot Projects Macula Lutea Algorithms Time Factors Wet Macular Degeneration ROC Curve Prognosis Middle Aged Imaging, Three-Dimensional Humans Retrospective Studies Disease Progression Support Vector Machine Female
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Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson's Disease in 3D Nuclear Imaging Data.

International journal of neural systems Mar 3, 2019
Over the last years convolutional neural networks (CNNs) have shown remarkable results in different image classification tasks, including medical imaging. One area that has been less explored with CNNs is Positron Emission Tomography (PET). Fluorodeo...
Humans Female Principal Component Analysis Neural Networks, Computer Positron-Emission Tomography Aged Male Functional Neuroimaging Parkinson Disease Brain Fluorodeoxyglucose F18 Middle Aged Imaging, Three-Dimensional Models, Statistical Case-Control Studies
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Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

Proceedings of the National Academy of Sciences of the United States of America Feb 26, 2019
A varying oxygen environment is known to affect cellular function in disease as well as activity of various therapeutics. For transient structures, whether they are unconstrained therapeutic transplants, migrating cells during tumor metastasis, or ce...
Mice, Inbred C57BL Oxygen Prostheses and Implants Immunity Imaging, Three-Dimensional Machine Learning Islets of Langerhans Transplantation Magnetic Resonance Imaging Animals Fluorine Cluster Analysis Biocompatible Materials Halogenation Insulin Secretion Partial Pressure Alginates
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DeepCEST: 9.4 T Chemical exchange saturation transfer MRI contrast predicted from 3 T data - a proof of concept study.

Magnetic resonance in medicine Feb 25, 2019
PURPOSE: To determine the feasibility of employing the prior knowledge of well-separated chemical exchange saturation transfer (CEST) signals in the 9.4 T Z-spectrum to separate overlapping CEST signals acquired at 3 T, using a deep learning approach...
Image Interpretation, Computer-Assisted Proof of Concept Study Brain Neoplasms Imaging, Three-Dimensional Contrast Media Humans Neural Networks, Computer Magnetic Resonance Imaging Brain
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