Suchergebnisse - Fully-automated segmentation algorithms*

Karpinski Score under Digital Investigation: A Fully Automated Segmentation Algorithm to Identify Vascular and Stromal Injury of Donors’ Kidneys von Salvi, Massimo, Mogetta, Alessandro, Meiburger, Kristen M., Gambella, Alessandro, Molinaro, Luca, Barreca, Antonella, Papotti, Mauro, Molinari, Filippo

“… In the present paper, the authors present a fully automated algorithm, called RENFAST (Rapid EvaluatioN of Fibrosis And vesselS Thickness …”
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fast, fully automated cell segmentation algorithm for high-throughput and high-content screening von Fenistein, D, Lenseigne, B, Christophe, T, Brodin, P, Genovesio, A

“… Time and robustness are paramount while accuracy is intrinsically statistical. In this article, a fast and fully automated algorithm for cell segmentation is proposed …”
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Fully Automated Segmentation Algorithm for Hematoma Volumetric Analysis in Spontaneous Intracerebral Hemorrhage von Ironside, Natasha, Chen, Ching-Jen, Mutasa, Simukayi, Sim, Justin L, Marfatia, Saurabh, Roh, David, Ding, Dale, Mayer, Stephan A, Lignelli, Angela, Connolly, Edward Sander

“… ). The aims of this study are to derive and validate a fully automated segmentation algorithm for ICH volumetric analysis using deep learning methods …”
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Fully Automated Segmentation Algorithm for Perihematomal Edema Volumetry After Spontaneous Intracerebral Hemorrhage von Ironside, Natasha, Chen, Ching-Jen, Mutasa, Simukayi, Sim, Justin L, Ding, Dale, Marfatiah, Saurabh, Roh, David, Mukherjee, Sugoto, Johnston, Karen C, Southerland, Andrew M, Mayer, Stephan A, Lignelli, Angela, Connolly, Edward Sander

“… The aims of this study are to derive and internally validate a fully automated segmentation algorithm for volumetric analysis of PHE …”
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Validation of a fully automated liver segmentation algorithm using multi-scale deep reinforcement learning and comparison versus manual segmentation von Winkel, David J., Weikert, Thomas J., Breit, Hanns-Christian, Chabin, Guillaume, Gibson, Eli, Heye, Tobias J., Comaniciu, Dorin, Boll, Daniel T.

“… To evaluate the performance of an artificial intelligence (AI) based software solution tested on liver volumetric analyses and to compare the results to the manual contour segmentation …”
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A computed tomography vertebral segmentation dataset with anatomical variations and multi-vendor scanner data von Liebl, Hans, Schinz, David, Sekuboyina, Anjany, Malagutti, Luca, Löffler, Maximilian T., Bayat, Amirhossein, El Husseini, Malek, Tetteh, Giles, Grau, Katharina, Niederreiter, Eva, Baum, Thomas, Wiestler, Benedikt, Menze, Bjoern, Braren, Rickmer, Zimmer, Claus, Kirschke, Jan S.

“… With the advent of deep learning algorithms, fully automated radiological image analysis is within reach …”
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Fully automated segmentation of the corticospinal tract using the TractSeg algorithm in patients with brain tumors von Richards, Tyler J., Anderson, Keri L., Anderson, Jeffrey S.

“… The objective is to validate a fully automated pipeline using the TractSeg algorithm (Wasserthal et al. NeuroImage 2018;183:239–253) to segment the corticospinal tract in patients with brain tumors adjacent to the corticospinal tract …”
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A Practical Guide to Manual and Semi-Automated Neurosurgical Brain Lesion Segmentation von Jain, Raunak, Lee, Faith, Luo, Nianhe, Hyare, Harpreet, Pandit, Anand S.

“… The purpose of the article is to provide a practical guide for manual and semi-automated image segmentation of common neurosurgical cranial lesions, namely meningioma, glioblastoma multiforme (GBM …”
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Crossword: A Fully Automated Algorithm for the Segmentation and Quality Control of Protein Microarray Images von Gierahn, Todd M, Loginov, Denis, Love, J. Christopher

“… In order to automate the extraction and curation of data from protein microarrays, we describe an algorithm called Crossword that logically combines information from multiple approaches to fully …”
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Fully automated waist circumference measurement on abdominal CT: Comparison with manual measurements and potential value for identifying overweight and obesity as an adjunct output of CT scan von Joo, Ijin, Kwak, Min-Sun, Park, Dae Hyun, Yoon, Soon Ho

“… We investigated a fully automated body segmentation algorithm for measuring WC on abdominal computed tomography (CT …”
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Liver Steatosis Categorization on Contrast-Enhanced CT Using a Fully Automated Deep Learning Volumetric Segmentation Tool: Evaluation in 1204 Healthy Adults Using Unenhanced CT as a Reference Standard von Pickhardt, Perry J, Blake, Glen M, Graffy, Peter M, Sandfort, Veit, Elton, Daniel C, Perez, Alberto A, Summers, Ronald M

“… CT using a fully automated deep learning volumetric hepatosplenic segmentation algorithm and unenhanced …”
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Fully automated segmentation of the left ventricle in cine cardiac MRI using neural network regression von Tan, Li Kuo, McLaughlin, Robert A., Lim, Einly, Abdul Aziz, Yang Faridah, Liew, Yih Miin

“… Purpose To develop and validate a fully automated neural network regression‐based algorithm for segmentation of the LV in cardiac MRI, with full coverage from apex …”
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Automated diagnosis and segmentation of choroidal neovascularization in OCT angiography using deep learning von Wang, Jie, Hormel, Tristan T., Gao, Liqin, Zang, Pengxiao, Guo, Yukun, Wang, Xiaogang, Bailey, Steven T., Jia, Yali

“… In this paper, a fully automated CNV diagnosis and segmentation algorithm using convolutional neural networks (CNNs) is described …”
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BraTS Toolkit: Translating BraTS Brain Tumor Segmentation Algorithms Into Clinical and Scientific Practice von Kofler, Florian, Berger, Christoph, Waldmannstetter, Diana, Lipkova, Jana, Ezhov, Ivan, Tetteh, Giles, Kirschke, Jan, Zimmer, Claus, Wiestler, Benedikt, Menze, Bjoern H.

“… Despite great advances in brain tumor segmentation and clear clinical need, translation of state-of-the-art computational methods into clinical routine and scientific practice remains a major challenge …”
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CT image segmentation for inflamed and fibrotic lungs using a multi-resolution convolutional neural network von Gerard, Sarah E., Herrmann, Jacob, Xin, Yi, Martin, Kevin T., Rezoagli, Emanuele, Ippolito, Davide, Bellani, Giacomo, Cereda, Maurizio, Guo, Junfeng, Hoffman, Eric A., Kaczka, David W., Reinhardt, Joseph M.

“… The purpose of this study was to develop a fully-automated segmentation algorithm, robust to various density enhancing lung abnormalities, to facilitate rapid quantitative analysis of computed tomography images …”
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Fully Automated Segmentation of Fluid/Cyst Regions in Optical Coherence Tomography Images With Diabetic Macular Edema Using Neutrosophic Sets and Graph Algorithms von Rashno, Abdolreza, Koozekanani, Dara D., Drayna, Paul M., Nazari, Behzad, Sadri, Saeed, Rabbani, Hossein, Parhi, Keshab K.

“… This paper presents a fully automated algorithm to segment fluid-associated (fluid-filled) and cyst regions in optical coherence tomography …”
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Deep learning-based muscle segmentation and quantification at abdominal CT: application to a longitudinal adult screening cohort for sarcopenia assessment von Graffy, Peter M., Liu, Jiamin, Pickhardt, Perry J., Burns, Joseph E., Yao, Jianhua, Summers, Ronald M.

“… A fully automated validated muscle segmentation algorithm was applied to 9310 non-contrast CT scans, including a primary screening cohort of 8037 consecutive asymptomatic adults (mean age, 57.1±7.8 years; 3555M/4482F …”
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Automated 3D MRI rendering of the craniofacial skeleton: using ZTE to drive the segmentation of black bone and FIESTA-C images von Eley, Karen A, Delso, Gaspar

“… Purpose Automated bone segmentation from MRI datasets would have a profound impact on clinical utility, particularly in the craniofacial skeleton where complex anatomy is coupled with radiosensitive organs …”
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Fully automated segmentation of callus by micro-CT compared to biomechanics von Bissinger, Oliver, Götz, Carolin, Wolff, Klaus-Dietrich, Hapfelmeier, Alexander, Prodinger, Peter Michael, Tischer, Thomas

“… Our aim was to therefore apply a fully automated segmentation algorithm to determine μCT parameters and examine their association with biomechanic …”
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Comparison of retinal layer thickness measurements obtained using two different swept-source optical coherence tomography imaging modes von Yoon, Yo Sep, Park, Chang Uk, Song, Jun Ho, Min, Jung Kee

“… Conclusions The full retinal thickness measurements determined using both fully automated segmentation algorithms …”
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