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Total 1855 results found since Jan 2013.
Aortic Annulus Detection Based on Deep Learning for Transcatheter Aortic Valve Replacement Using Cardiac Computed Tomography
CONCLUSION: Our deep learning framework was feasible to detect the 3D complex structure of the aortic annulus plane using cardiac CT for TAVR. The performance of our algorithms was higher than other convolutional neural networks.PMID:37724499 | DOI:10.3346/jkms.2023.38.e306
Source: J Korean Med Sci - September 19, 2023 Category: General Medicine Authors: Yongwon Cho Soojung Park Sung Ho Hwang Minseok Ko Do-Sun Lim Cheol Woong Yu Seong-Mi Park Mi-Na Kim Yu-Whan Oh Guang Yang Source Type: research
Smell and Taste Disorders in Primary Care
Am Fam Physician. 2023 Sep;108(3):240-248.ABSTRACTDisorders of smell and taste are reported by approximately one-fifth of people 40 years and older, and one-third of people 80 years and older. These disorders affect quality of life and the ability to identify smoke and toxins. Smell and taste disorders can be early signs of dementia or Parkinson disease and are associated with increased mortality. Dysfunction may be apparent or may develop insidiously. Screening questionnaires are available, but many patients are unaware of their disorder. Most smell and taste disorders are due to sinonasal disease but also could be caused...
Source: American Family Physician - September 19, 2023 Category: Primary Care Authors: Dillon J Savard Francesca G Ursua Heidi L Gaddey Source Type: research
Cone beam computed tomography image guidance within a magnetic resonance imaging-only planning workflow
CONCLUSION: The results of this study support the concept that with focussed training, an MRI to CBCT image guidance approach can be successfully implemented in a clinical planning workflow.PMID:37720461 | PMC:PMC10500022 | DOI:10.1016/j.phro.2023.100472
Source: Health Physics - September 18, 2023 Category: Physics Authors: Laura M O'Connor Alesha Quinn Samuel Denley Lucy Leigh Jarad Martin Jason A Dowling Kate Skehan Helen Warren-Forward Peter B Greer Source Type: research
TransQA: deep hybrid transformer network for measurement-guided volumetric dose prediction of pre-treatment patient-specific quality assurance
Phys Med Biol. 2023 Sep 15. doi: 10.1088/1361-6560/acfa5e. Online ahead of print.ABSTRACTOBJECTIVE: Performing pre-treatment patient-specific quality assurance (prePSQA) is considered an essential, time-consuming, and resource-intensive task for volumetric modulated arc radiotherapy (VMAT) which confirms the dose accuracy and ensure patient safety. Most current machine learning and deep learning approaches stack excessive convolutional/pooling operations (CPs) to predict prePSQA with two-dimensional or one-dimensional information input. However, these models generally present limitations in explicitly modeling long-range d...
Source: Physics in Medicine and Biology - September 15, 2023 Category: Physics Authors: Lingpeng Zeng Minghui Zhang Yun Zhang Zhongsheng Zou Yu Guan Bin Huang Xiuwen Yu Shenggou Ding Qiegen Liu Changfei Gong Source Type: research
Computed tomography angiography-based radiomics model to identify high-risk carotid plaques
CONCLUSIONS: The combined model of the radiomics features of carotid plaques and PVAT and the traditional CTA features significantly contributes to identifying high-risk carotid plaques compared with traditional CTA model.PMID:37711840 | PMC:PMC10498225 | DOI:10.21037/qims-23-158
Source: Atherosclerosis - September 15, 2023 Category: Cardiology Authors: Chao Chen Wei Tang Yong Chen Wenhan Xu Ningjun Yu Chao Liu Zenghui Li Zhao Tang Xiaoming Zhang Source Type: research
TransQA: deep hybrid transformer network for measurement-guided volumetric dose prediction of pre-treatment patient-specific quality assurance
Phys Med Biol. 2023 Sep 15. doi: 10.1088/1361-6560/acfa5e. Online ahead of print.ABSTRACTOBJECTIVE: Performing pre-treatment patient-specific quality assurance (prePSQA) is considered an essential, time-consuming, and resource-intensive task for volumetric modulated arc radiotherapy (VMAT) which confirms the dose accuracy and ensure patient safety. Most current machine learning and deep learning approaches stack excessive convolutional/pooling operations (CPs) to predict prePSQA with two-dimensional or one-dimensional information input. However, these models generally present limitations in explicitly modeling long-range d...
Source: Physics in Medicine and Biology - September 15, 2023 Category: Physics Authors: Lingpeng Zeng Minghui Zhang Yun Zhang Zhongsheng Zou Yu Guan Bin Huang Xiuwen Yu Shenggou Ding Qiegen Liu Changfei Gong Source Type: research
Computed tomography angiography-based radiomics model to identify high-risk carotid plaques
CONCLUSIONS: The combined model of the radiomics features of carotid plaques and PVAT and the traditional CTA features significantly contributes to identifying high-risk carotid plaques compared with traditional CTA model.PMID:37711840 | PMC:PMC10498225 | DOI:10.21037/qims-23-158
Source: Atherosclerosis - September 15, 2023 Category: Cardiology Authors: Chao Chen Wei Tang Yong Chen Wenhan Xu Ningjun Yu Chao Liu Zenghui Li Zhao Tang Xiaoming Zhang Source Type: research
CT-based non-invasive identification of the most common gene mutation status in patients with non-small cell lung cancer
CONCLUSIONS: Our study demonstrates the potential of radiomics in the non-invasive identification of EGFR and KRAS mutation status, which may guide patients with non-small cell lung cancer to choose the most appropriate personalized treatment. This method can be used when biopsy will bring unacceptable risk to patients with NSCLC.PMID:37706584 | DOI:10.1002/mp.16744
Source: Health Physics - September 14, 2023 Category: Physics Authors: Zongjian Chen Si Gao Changwei Ding Ting Luo Jiaqi Xu Shuang Xu Shu Li Source Type: research
Proton range uncertainty caused by synthetic computed tomography generated with deep learning from pelvic magnetic resonance imaging
CONCLUSION: The sCT model was shown to be robust, i.e., had a low random model error. However, further investigation to reduce and even predict and manage systematic error is still needed for future MRI-only proton therapy.PMID:37703314 | DOI:10.1080/0284186X.2023.2256967
Source: Acta Oncologica - September 13, 2023 Category: Cancer & Oncology Authors: Liheng Tian Armin L ühr Source Type: research
Predicting successful clinical candidates for fiducial-free lung tumor tracking with a deep learning binary classification model
CONCLUSIONS: A deep learning model can distinguish features of trackable and untrackable lesions in DRR images, and can predict successful candidates for fiducial-free lung tumor tracking.PMID:37696265 | DOI:10.1002/acm2.14146
Source: Journal of Applied Clinical Medical Physics - September 11, 2023 Category: Physics Authors: Matthieu Lafreni ère Gilmer Valdes Martina Descovich Source Type: research
