MARC details
| 000 -LEADER |
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| fixed length control field |
03227nam a22003617a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
220222s20222022 xxu||||| |||| 00| 0 eng d |
| 024 ## - OTHER STANDARD IDENTIFIER |
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| Standard number or code |
10.3389/fcvm.2022.822269 [doi] |
| 024 ## - OTHER STANDARD IDENTIFIER |
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| Standard number or code |
PMC8831539 [pmc] |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
Ovid MEDLINE(R) |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
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| PMID |
35155637 |
| 245 ## - TITLE STATEMENT |
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| Title |
Generalizable Framework for Atrial Volume Estimation for Cardiac CT Images Using Deep Learning With Quality Control Assessment. |
| 251 ## - Source |
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| Source |
Frontiers in Cardiovascular Medicine. 9:822269, 2022. |
| 252 ## - Abbreviated Source |
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| Abbreviated source |
Front. cardiovasc. med.. 9:822269, 2022. |
| 253 ## - Journal Name |
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| Journal name |
Frontiers in cardiovascular medicine |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Year |
2022 |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Manufacturer |
FY2022 |
| 265 ## - SOURCE FOR ACQUISITION/SUBSCRIPTION ADDRESS [OBSOLETE] |
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| Publication status |
epublish |
| 266 ## - Date added to catalog |
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| Date added to catalog |
2022-02-22 |
| 520 ## - SUMMARY, ETC. |
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| Abstract |
Conclusions: We proposed a generalizable framework that consists of DL models and computational methods for LAV estimation. The framework provides an efficient and robust strategy for QC assessment of the accuracy for DL-based image segmentation and volume estimation tasks, allowing high-throughput extraction of reproducible LAV measurements to be possible. Copyright (c) 2022 Abdulkareem, Brahier, Zou, Taylor, Thomaides, Bergquist, Srichai, Lee, Vargas and Petersen. |
| 520 ## - SUMMARY, ETC. |
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| Abstract |
Methods: Using a dataset of 85,477 CCT images from 337 patients, we proposed a framework that consists of several processes that perform a combination of tasks including the selection of images with LA from all other images using a ResNet50 classification model, the segmentation of images with LA using a UNet image segmentation model, the assessment of the quality of the image segmentation task, the estimation of LAV, and quality control (QC) assessment. |
| 520 ## - SUMMARY, ETC. |
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| Abstract |
Objectives: Cardiac computed tomography (CCT) is a common pre-operative imaging modality to evaluate pulmonary vein anatomy and left atrial appendage thrombus in patients undergoing catheter ablation (CA) for atrial fibrillation (AF). These images also allow for full volumetric left atrium (LA) measurement for recurrence risk stratification, as larger LA volume (LAV) is associated with higher recurrence rates. Our objective is to apply deep learning (DL) techniques to fully automate the computation of LAV and assess the quality of the computed LAV values. |
| 520 ## - SUMMARY, ETC. |
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| Abstract |
Results: Overall, the proposed LAV estimation framework achieved accuracies of 98% (precision, recall, and F1 score metrics) in the image classification task, 88.5% (mean dice score) in the image segmentation task, 82% (mean dice score) in the segmentation quality prediction task, and R 2 (the coefficient of determination) value of 0.968 in the volume estimation task. It correctly identified 9 out of 10 poor LAV estimations from a total of 337 patients as poor-quality estimates. |
| 546 ## - LANGUAGE NOTE |
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| Language note |
English |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
IN PROCESS -- NOT YET INDEXED |
| 651 ## - SUBJECT ADDED ENTRY--GEOGRAPHIC NAME |
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| Institution |
MedStar Heart & Vascular Institute |
| 657 ## - INDEX TERM--FUNCTION |
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| Medline publication type |
Journal Article |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Local Authors |
Bergquist, Peter J |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Local Authors |
Srichai, Monvadi B |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Local Authors |
Thomaides, Athanasios |
| 790 ## - Authors |
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| All authors |
Abdulkareem M, Bergquist PJ, Brahier MS, Lee AM, Petersen SE, Srichai MB, Taylor A, Thomaides A, Vargas JD, Zou F |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
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| DOI |
<a href="https://dx.doi.org/10.3389/fcvm.2022.822269">https://dx.doi.org/10.3389/fcvm.2022.822269</a> |
| Public note |
https://dx.doi.org/10.3389/fcvm.2022.822269 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Koha item type |
Journal Article |
| Item type description |
Article |
