Fully automatic
View article: Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? Open
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has t…
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Lung Infection Quantification of COVID-19 in CT Images with Deep Learning Open
CT imaging is crucial for diagnosis, assessment and staging COVID-19 infection. Follow-up scans every 3-5 days are often recommended for disease progression. It has been reported that bilateral and peripheral ground glass opacification (GG…
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Abnormal lung quantification in chest CT images of COVID‐19 patients with deep learning and its application to severity prediction Open
Objective Computed tomography (CT) provides rich diagnosis and severity information of COVID‐19 in clinical practice. However, there is no computerized tool to automatically delineate COVID‐19 infection regions in chest CT scans for quanti…
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Automatic Measurement of Chew Count and Chewing Rate during Food Intake Open
Research suggests that there might be a relationship between chew count as well as chewing rate and energy intake. Chewing has been used in wearable sensor systems for the automatic detection of food intake, but little work has been report…
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Reducing inter-observer variability and interaction time of MR liver volumetry by combining automatic CNN-based liver segmentation and manual corrections Open
The quality of automatic liver segmentations is on par with those from manual routines. Using automatic liver masks in the clinical workflow could lead to a reduction of segmentation time and a more consistent liver volume estimation acros…
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Fully automatic segmentation of left atrium and pulmonary veins in late gadolinium‐enhanced MRI: Towards objective atrial scar assessment Open
Purpose To realize objective atrial scar assessment, this study aimed to develop a fully automatic method to segment the left atrium (LA) and pulmonary veins (PV) from late gadolinium‐enhanced (LGE) magnetic resonance imaging (MRI). The ex…
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Automatic identification of coronary tree anatomy in coronary computed tomography angiography Open
An automatic coronary artery tree labeling algorithm is described to identify the anatomical segments of the extracted centerlines from coronary computed tomography angiography (CCTA) images. This method will facilitate the automatic lesio…
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Automatic Mexican Sign Language Recognition Using Normalized Moments and Artificial Neural Networks Open
This document presents a computer vision system for the automatic recognition of Mexican Sign Language (MSL), based on normalized moments as invariant (to translation and scale transforms) descriptors, using artificial neural networks as p…
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Automatic 3D aortic annulus sizing by computed tomography in the planning of transcatheter aortic valve implantation Open
The proposed automatic framework provides an accurate and robust tool for AoA measurements and THV sizing in patients undergoing TAVI.
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From Controlled to Automatic Processes and Back Again: The Role of Contextual Features Open
In cognitive psychology, classical approaches categorize automatic and controlled processes from a dichotomous point of view. Automatic processes are believed to be rigid, whereas controlled processes are thought to be flexible. New theori…
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Application of nnU-Net for Automatic Segmentation of Lung Lesions on CT Images and Its Implication for Radiomic Models Open
Radiomics investigates the predictive role of quantitative parameters calculated from radiological images. In oncology, tumour segmentation constitutes a crucial step of the radiomic workflow. Manual segmentation is time-consuming and pron…
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Supervised Learning of Automatic Pyramid for Optimization-Based Multi-Document Summarization Open
We present a new supervised framework that learns to estimate automatic Pyramid scores and uses them for optimization-based extractive multi-document summarization. For learning automatic Pyramid scores, we developed a method for automatic…
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Beyond automatic medical image segmentation—the spectrum between fully manual and fully automatic delineation Open
Semi-automatic and fully automatic contouring tools have emerged as an alternative to fully manual segmentation to reduce time spent contouring and to increase contour quality and consistency. Particularly, fully automatic segmentation has…
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Image Analysis Pipeline for Renal Allograft Evaluation and Fibrosis Quantification Open
This pipeline can automatically and accurately detect glomeruli and select cortical ROIs that can easily be used to develop, validate, and apply image analysis algorithms.
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Automatic identification and segmentation of slice of minimal hiatal dimensions in transperineal ultrasound volumes Open
Objective To develop and validate a tool for automatic selection of the slice of minimal hiatal dimensions (SMHD) and segmentation of the urogenital hiatus (UH) in transperineal ultrasound (TPUS) volumes. Methods Manual selection of the SM…
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DeXtrusion: automatic recognition of epithelial cell extrusion through machine learning <i>in vivo</i> Open
Accurately counting and localising cellular events from movies is an important bottleneck of high-content tissue/embryo live imaging. Here, we propose a new methodology based on deep learning that allows automatic detection of cellular eve…
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Automatic snoring detection using a hybrid 1D–2D convolutional neural network Open
Snoring, as a prevalent symptom, seriously interferes with life quality of patients with sleep disordered breathing only (simple snorers), patients with obstructive sleep apnea (OSA) and their bed partners. Researches have shown that snori…
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Automatic structural scene digitalization Open
In this paper, we present an automatic system for the analysis and labeling of structural scenes, floor plan drawings in Computer-aided Design (CAD) format. The proposed system applies a fusion strategy to detect and recognize various comp…
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A robust multi-variability model based liver segmentation algorithm for CT-scan and MRI modalities Open
Developing methods to segment the liver in medical images, study and analyze it remains a significant challenge. The shape of the liver can vary considerably from one patient to another, and adjacent organs are visualized in medical images…
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Automatic Assessment of Lower-Limb Alignment from Computed Tomography Open
Background: Preoperative planning of lower-limb realignment surgical procedures necessitates the quantification of alignment parameters by using landmarks placed on medical scans. Conventionally, alignment measurements are performed on 2-d…
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Comparison of liver volumetry on contrast‐enhanced CT images: one semiautomatic and two automatic approaches Open
This study was to evaluate the accuracy, consistency, and efficiency of three liver volumetry methods— one interactive method, an in‐house‐developed 3D medical Image Analysis (3DMIA) system, one automatic active shape model (ASM)‐based seg…
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A Robust, Fully Automatic Detection Method and Calculation Technique of Midline Shift in Intracranial Hemorrhage and Its Clinical Application Open
A midline shift (MLS) is an important clinical indicator for intracranial hemorrhage. In this study, we proposed a robust, fully automatic neural network-based model for the detection of MLS and compared it with MLSs drawn by clinicians; w…
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Automatic Spinal Cord Gray Matter Quantification: A Novel Approach Open
Our novel approach including the averaged magnetization inversion recovery acquisitions sequence and a fully-automated postprocessing segmentation algorithm demonstrated an accurate and reproducible spinal cord GM and WM segmentation. This…
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An automatic facial landmarking for children with rare diseases Open
Two to three thousand syndromes modify facial features: their screening requires the eye of an expert in dysmorphology. A widely used tool in shape characterization is geometric morphometrics based on landmarks, which are precise and repro…
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Aortic root evaluation prior to transcatheter aortic valve implantation—Correlation of manual and semi-automatic measurements Open
Use of semi-automatic software in pre-TAVI evaluation results in comparable results in respect of measurements and selected valve prosthesis size, while necessary reading time is significantly lower.
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Automatic Assessment of Keel Bone Damage in Laying Hens at the Slaughter Line Open
Keel bone damage (KBD) can be found in all commercial laying hen flocks with a wide range of 23% to 69% of hens/flock found to be affected in this study. As KBD may be linked with chronic pain and a decrease in mobility, it is a serious we…
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A Web-Based Platform for the Automatic Stratification of ARDS Severity Open
Acute respiratory distress syndrome (ARDS), including severe pulmonary COVID infection, is associated with a high mortality rate. It is crucial to detect ARDS early, as a late diagnosis may lead to serious complications in treatment. One o…
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Automatic cerebrovascular segmentation methods-a review Open
Cerebrovascular diseases are one of the serious causes for the increase in mortality rate in the world which affect the blood vessels and blood supply to the brain. In order, diagnose and study the abnormalities in the cerebrovascular syst…
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Workflow for automatic renal perfusion quantification using ASL‐MRI and machine learning Open
Purpose Clinical applicability of renal arterial spin labeling (ASL) MRI is hampered because of time consuming and observer dependent post‐processing, including manual segmentation of the cortex to obtain cortical renal blood flow (RBF). M…
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Evaluation of Deep Learning-Based Automatic Floor Plan Analysis Technology: An AHP-Based Assessment Open
This study proposes a technology that allows automatic extraction of vectorized indoor spatial information from raster images of floor plans. Automatic reconstruction of indoor spaces from floor plans is based on a deep learning algorithm,…