AIMC Topic: Subtraction Technique
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Deep learning-based arterial subtraction images improve the detection of LR-TR algorithm for viable HCC on extracellular agents-enhanced MRI.
Abdominal radiology (New York)
Apr 20, 2024
PURPOSE: To determine the role of deep learning-based arterial subtraction images in viability assessment on extracellular agents-enhanced MRI using LR-TR algorithm.
Male
Middle Aged
Deep Learning
Liver Neoplasms
Aged, 80 and over
Adult
Sensitivity and Specificity
Humans
Image Interpretation, Computer-Assisted
Female
Image Enhancement
Aged
Angiography, Digital Subtraction
Algorithms
Subtraction Technique
Retrospective Studies
Carcinoma, Hepatocellular
Contrast Media
Magnetic Resonance Imaging
Coronary Artery Stent Evaluation by CTA: Impact of Deep Learning Reconstruction and Subtraction Technique.
AJR. American journal of roentgenology
Aug 10, 2022
Coronary CTA with hybrid iterative reconstruction (HIR) is prone to false-positive results for in-stent restenosis due to stent-related blooming artifact. The purpose of this study is to assess the impact of deep learning reconstruction (DLR), subt...
Effectiveness of temporal subtraction computed tomography images using deep learning in detecting vertebral bone metastases.
European journal of radiology
Jul 20, 2022
PURPOSE: To assess the clinical effectiveness of temporal subtraction computed tomography (TS CT) using deep learning to improve vertebral bone metastasis detection.
Fusing Self-Organized Neural Network and Keypoint Clustering for Localized Real-Time Background Subtraction.
International journal of neural systems
Mar 2, 2020
Moving object detection in video streams plays a key role in many computer vision applications. In particular, separation between background and foreground items represents a main prerequisite to carry out more complex tasks, such as object classific...
Adaptive weighted log subtraction based on neural networks for markerless tumor tracking using dual-energy fluoroscopy.
Medical physics
Jan 10, 2020
PURPOSE: To present a novel method, based on convolutional neural networks (CNN), to automate weighted log subtraction (WLS) for dual-energy (DE) fluoroscopy to be used in conjunction with markerless tumor tracking (MTT).
Segmentation of Fetal Left Ventricle in Echocardiographic Sequences Based on Dynamic Convolutional Neural Networks.
IEEE transactions on bio-medical engineering
Nov 15, 2016
Segmentation of fetal left ventricle (LV) in echocardiographic sequences is important for further quantitative analysis of fetal cardiac function. However, image gross inhomogeneities and fetal random movements make the segmentation a challenging pro...
Mammogram Enhancement Using Intuitionistic Fuzzy Sets.
IEEE transactions on bio-medical engineering
Nov 2, 2016
OBJECTIVE: Conventional mammogram enhancement methods use transform-domain filtering, which possibly produce some artifacts or not well highlight all local details in images. This paper presents a new enhancement method based on intuitionistic fuzzy ...
Pulmonary Nodule Detection Model Based on SVM and CT Image Feature-Level Fusion with Rough Sets.
BioMed research international
Sep 18, 2016
In order to improve the detection accuracy of pulmonary nodules in CT image, considering two problems of pulmonary nodules detection model, including unreasonable feature structure and nontightness of feature representation, a pulmonary nodules detec...
Efficient Descriptor-Based Segmentation of Parotid Glands With Nonlocal Means.
IEEE transactions on bio-medical engineering
Sep 16, 2016
OBJECTIVE: We introduce descriptor-based segmentation that extends existing patch-based methods by combining intensities, features, and location information. Since it is unclear which image features are best suited for patch selection, we perform a b...
Task-Driven Dictionary Learning Based on Mutual Information for Medical Image Classification.
IEEE transactions on bio-medical engineering
Sep 1, 2016
OBJECTIVE: We present a novel variant of the bag-of-visual-words (BoVW) method for automated medical image classification.
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