AIMC Topic: Image Processing, Computer-Assisted

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Evaluation of Deep Learning Models for Identifying Surgical Actions and Measuring Performance.

JAMA network open Mar 2, 2020
IMPORTANCE: When evaluating surgeons in the operating room, experienced physicians must rely on live or recorded video to assess the surgeon's technical performance, an approach prone to subjectivity and error. Owing to the large number of surgical p...
Image Processing, Computer-Assisted Video Recording Surgical Procedures, Operative Surgical Instruments Surgeons Deep Learning Clinical Competence Humans Algorithms
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Deep learning-based attenuation correction in the absence of structural information for whole-body positron emission tomography imaging.

Physics in medicine and biology Mar 2, 2020
Deriving accurate structural maps for attenuation correction (AC) of whole-body positron emission tomography (PET) remains challenging. Common problems include truncation, inter-scan motion, and erroneous transformation of structural voxel-intensitie...
Humans Retrospective Studies Whole Body Imaging Positron Emission Tomography Computed Tomography Artifacts Reproducibility of Results Movement Deep Learning Image Processing, Computer-Assisted
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A Deep Learning-based correction to EPID dosimetry for attenuation and scatter in the Unity MR-Linac system.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Mar 2, 2020
PURPOSE: EPID dosimetry in the Unity MR-Linac system allows for reconstruction of absolute dose distributions within the patient geometry. Dose reconstruction is accurate for the parts of the beam arriving at the EPID through the MRI central unattenu...
Magnetic Resonance Imaging Rectal Neoplasms Radiotherapy Planning, Computer-Assisted Reproducibility of Results Deep Learning Image Processing, Computer-Assisted Radiometry Radiotherapy, Intensity-Modulated Scattering, Radiation Phantoms, Imaging Humans Algorithms
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Catheter segmentation in X-ray fluoroscopy using synthetic data and transfer learning with light U-nets.

Computer methods and programs in biomedicine Feb 29, 2020
Background and objectivesAutomated segmentation and tracking of surgical instruments and catheters under X-ray fluoroscopy hold the potential for enhanced image guidance in catheter-based endovascular procedures. This article presents a novel method ...
Neural Networks, Computer X-Rays Deep Learning Humans Fluoroscopy Image Processing, Computer-Assisted Surgery, Computer-Assisted Catheters
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A convolutional neural network-based model observer for breast CT images.

Medical physics Feb 29, 2020
PURPOSE: In this paper, we propose a convolutional neural network (CNN)-based efficient model observer for breast computed tomography (CT) images.
Normal Distribution Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted Least-Squares Analysis Breast Signal-To-Noise Ratio
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Content-aware specular reflection suppression based on adaptive image inpainting and neural network for endoscopic images.

Computer methods and programs in biomedicine Feb 28, 2020
In this article, a content-aware specular reflection suppression scheme was developed based on adaptive image inpainting and neural network for endoscopic images. To decrease the impact of specular reflection on visual quality, the proposed scheme co...
Image Processing, Computer-Assisted Image Enhancement Neural Networks, Computer Algorithms Endoscopy
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CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.

European radiology Feb 28, 2020
PURPOSE: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. The aims of this study are to develop and validate a computed tomography ...
Neoplasm Invasiveness Neoplasm Recurrence, Local Adenocarcinoma of Lung Humans Image Processing, Computer-Assisted Lung Neoplasms Female Logistic Models Risk Factors Male Machine Learning Sensitivity and Specificity Retrospective Studies Middle Aged Tomography, X-Ray Computed ROC Curve
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Automatic labeling of cortical sulci using patch- or CNN-based segmentation techniques combined with bottom-up geometric constraints.

Medical image analysis Feb 28, 2020
The extreme variability of the folding pattern of the human cortex makes the recognition of cortical sulci, both automatic and manual, particularly challenging. Reliable identification of the human cortical sulci in its entirety, is extremely difficu...
Machine Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Real-time markerless tumour tracking with patient-specific deep learning using a personalised data generation strategy: proof of concept by phantom study.

The British journal of radiology Feb 28, 2020
OBJECTIVE: For real-time markerless tumour tracking in stereotactic lung radiotherapy, we propose a different approach which uses patient-specific deep learning (DL) using a personalised data generation strategy, avoiding the need for collection of a...
Humans Deep Learning Image Processing, Computer-Assisted Phantoms, Imaging Movement Four-Dimensional Computed Tomography Lung Neoplasms Fluoroscopy Feasibility Studies
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Calculating the target exposure index using a deep convolutional neural network and a rule base.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Feb 27, 2020
PURPOSE: The objective of this study is to determine the quality of chest X-ray images using a deep convolutional neural network (DCNN) and a rule base without performing any visual assessment. A method is proposed for determining the minimum diagnos...
Sensitivity and Specificity Middle Aged Lung Aged, 80 and over Young Adult Adult Radiography, Thoracic Thorax Mediastinum Deep Learning Image Processing, Computer-Assisted Spine Humans Tomography, X-Ray Computed Neural Networks, Computer Reproducibility of Results Aged
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