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Detection of left b...
Detection of left bundle branch block and obstructive coronary artery disease from myocardial perfusion scintigraphy using deep neural networks
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- Arvidsson, Ida (författare)
- Lund University,Lunds universitet,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH,Lund Univ, Sweden
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- Overgaard, Niels Christian (författare)
- Lund University,Lunds universitet,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH,Lund Univ, Sweden
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- Davidsson, Anette (författare)
- Linköpings universitet,Linköping University,Avdelningen för diagnostik och specialistmedicin,Medicinska fakulteten,Region Östergötland, Fysiologiska kliniken US
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- Frias Rose, Miguel Jeronimo (författare)
- Linköpings universitet,Linköping University,Avdelningen för neurobiologi,Medicinska fakulteten
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- Aström, Kalle (författare)
- Lund University,Lunds universitet,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH,Lund Univ, Sweden
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- Figueroa, Miguel Ochoa (författare)
- Linköpings universitet,Linköping University,Institutionen för hälsa, medicin och vård,Medicinska fakulteten,Centrum för medicinsk bildvetenskap och visualisering, CMIV,Region Östergötland, Fysiologiska kliniken US,Region Östergötland, Röntgenkliniken i Linköping
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- Heyden, Anders (författare)
- Lund University,Lunds universitet,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH,Lund Univ, Sweden
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Mazurowski, Maciej A. (redaktör/utgivare)
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Drukker, Karen (redaktör/utgivare)
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(creator_code:org_t)
- SPIE, 2021
- 2021
- Engelska.
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Ingår i: Medical Imaging 2021 : Computer-Aided Diagnosis - Computer-Aided Diagnosis. - : SPIE. - 1605-7422. - 9781510640238 ; 11597
- Relaterad länk:
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http://dx.doi.org/10...
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https://lup.lub.lu.s...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Myocardial perfusion scintigraphy, which is a non-invasive imaging technique, is one of the most common cardiological examinations performed today, and is used for diagnosis of coronary artery disease. Currently the analysis is performed visually by physicians, but this is both a very time consuming and a subjective approach. These are two of the motivations for why an automatic tool to support the decisions would be useful. We have developed a deep neural network which predicts the occurrence of obstructive coronary artery disease in each of the three major arteries as well as left bundle branch block. Since multiple, or none, of these could have a defect, this is treated as a multi-label classification problem. Due to the highly imbalanced labels, the training loss is weighted accordingly. The prediction is based on two polar maps, captured during stress in upright and supine position, together with additional information such as BMI and angina symptoms. The polar maps are constructed from myocardial perfusion scintigraphy examinations conducted in a dedicated Cadmium-Zinc-Telluride cardio camera (D-SPECT Spectrum Dynamics). The study includes data from 759 patients. Using 5-fold cross-validation we achieve an area under the receiver operating characteristics curve of 0.89 as average on per-vessel level for the three major arteries, 0.94 on per-patient level and 0.82 for left bundle branch block.
Ämnesord
- NATURVETENSKAP -- Matematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
Nyckelord
- Convolutional neural network
- Deep learning
- Left bundle branch block
- Obstructive coronary artery disease
- Obstructive coronary artery disease; left bundle branch block; deep learning; convolutional neural network
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)
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