BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

519 related articles for article (PubMed ID: 35394183)

  • 1. Automatic coronary artery segmentation and diagnosis of stenosis by deep learning based on computed tomographic coronary angiography.
    Li Y; Wu Y; He J; Jiang W; Wang J; Peng Y; Jia Y; Xiong T; Jia K; Yi Z; Chen M
    Eur Radiol; 2022 Sep; 32(9):6037-6045. PubMed ID: 35394183
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep learning analysis in coronary computed tomographic angiography imaging for the assessment of patients with coronary artery stenosis.
    Han D; Liu J; Sun Z; Cui Y; He Y; Yang Z
    Comput Methods Programs Biomed; 2020 Nov; 196():105651. PubMed ID: 32712571
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Improving CCTA-based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation.
    Freiman M; Nickisch H; Prevrhal S; Schmitt H; Vembar M; Maurovich-Horvat P; Donnelly P; Goshen L
    Med Phys; 2017 Mar; 44(3):1040-1049. PubMed ID: 28112409
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Combination of computed tomography angiography with coronary artery calcium score for improved diagnosis of coronary artery disease: a collaborative meta-analysis of stable chest pain patients referred for invasive coronary angiography.
    Mohamed M; Bosserdt M; Wieske V; Dubourg B; Alkadhi H; Garcia MJ; Leschka S; Zimmermann E; Shabestari AA; Nørgaard BL; Meijs MFL; Øvrehus KA; Diederichsen ACP; Knuuti J; Halvorsen BA; Mendoza-Rodriguez V; Wan YL; Bettencourt N; Martuscelli E; Buechel RR; Mickley H; Sun K; Muraglia S; Kaufmann PA; Herzog BA; Tardif JC; Schütz GM; Laule M; Newby DE; Achenbach S; Budoff M; Haase R; Biavati F; Mézquita AV; Schlattmann P; Dewey M;
    Eur Radiol; 2024 Apr; 34(4):2426-2436. PubMed ID: 37831139
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Clinical Evaluation of the Automatic Coronary Artery Disease Reporting and Data System (CAD-RADS) in Coronary Computed Tomography Angiography Using Convolutional Neural Networks.
    Huang Z; Xiao J; Wang X; Li Z; Guo N; Hu Y; Li X; Wang X
    Acad Radiol; 2023 Apr; 30(4):698-706. PubMed ID: 35753936
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic coronary plaque detection, classification, and stenosis grading using deep learning and radiomics on computed tomography angiography images: a multi-center multi-vendor study.
    Jin X; Li Y; Yan F; Liu Y; Zhang X; Li T; Yang L; Chen H
    Eur Radiol; 2022 Aug; 32(8):5276-5286. PubMed ID: 35290509
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Artificial intelligence evaluation of coronary computed tomography angiography for coronary stenosis classification and diagnosis.
    Lee DY; Chang CC; Ko CF; Lee YH; Tsai YL; Chou RH; Chang TY; Guo SM; Huang PH
    Eur J Clin Invest; 2024 Jan; 54(1):e14089. PubMed ID: 37668089
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis.
    Zreik M; Lessmann N; van Hamersvelt RW; Wolterink JM; Voskuil M; Viergever MA; Leiner T; Išgum I
    Med Image Anal; 2018 Feb; 44():72-85. PubMed ID: 29197253
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Diagnostic performance of coronary computed tomography angiography stenosis score for coronary stenosis.
    Xiong QF; Fu XR; Ku LZ; Zhou D; Guo SP; Zhang WS
    BMC Med Imaging; 2024 Feb; 24(1):39. PubMed ID: 38336622
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automated left ventricular myocardium segmentation using 3D deeply supervised attention U-net for coronary computed tomography angiography; CT myocardium segmentation.
    Jun Guo B; He X; Lei Y; Harms J; Wang T; Curran WJ; Liu T; Jiang Zhang L; Yang X
    Med Phys; 2020 Apr; 47(4):1775-1785. PubMed ID: 32017118
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Evaluation of a deep learning model on coronary CT angiography for automatic stenosis detection.
    Paul JF; Rohnean A; Giroussens H; Pressat-Laffouilhere T; Wong T
    Diagn Interv Imaging; 2022 Jun; 103(6):316-323. PubMed ID: 35090845
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deep learning analysis of left ventricular myocardium in CT angiographic intermediate-degree coronary stenosis improves the diagnostic accuracy for identification of functionally significant stenosis.
    van Hamersvelt RW; Zreik M; Voskuil M; Viergever MA; Išgum I; Leiner T
    Eur Radiol; 2019 May; 29(5):2350-2359. PubMed ID: 30421020
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep learning-based noise reduction for coronary CT angiography: using four-dimensional noise-reduction images as the ground truth.
    Kobayashi T; Nishii T; Umehara K; Ota J; Ohta Y; Fukuda T; Ishida T
    Acta Radiol; 2023 May; 64(5):1831-1840. PubMed ID: 36475893
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry.
    van Rosendael AR; Maliakal G; Kolli KK; Beecy A; Al'Aref SJ; Dwivedi A; Singh G; Panday M; Kumar A; Ma X; Achenbach S; Al-Mallah MH; Andreini D; Bax JJ; Berman DS; Budoff MJ; Cademartiri F; Callister TQ; Chang HJ; Chinnaiyan K; Chow BJW; Cury RC; DeLago A; Feuchtner G; Hadamitzky M; Hausleiter J; Kaufmann PA; Kim YJ; Leipsic JA; Maffei E; Marques H; Pontone G; Raff GL; Rubinshtein R; Shaw LJ; Villines TC; Gransar H; Lu Y; Jones EC; Peña JM; Lin FY; Min JK
    J Cardiovasc Comput Tomogr; 2018; 12(3):204-209. PubMed ID: 29753765
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep learning powered coronary CT angiography for detecting obstructive coronary artery disease: The effect of reader experience, calcification and image quality.
    Liu CY; Tang CX; Zhang XL; Chen S; Xie Y; Zhang XY; Qiao HY; Zhou CS; Xu PP; Lu MJ; Li JH; Lu GM; Zhang LJ
    Eur J Radiol; 2021 Sep; 142():109835. PubMed ID: 34237493
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A token-mixer architecture for CAD-RADS classification of coronary stenosis on multiplanar reconstruction CT images.
    Penso M; Moccia S; Caiani EG; Caredda G; Lampus ML; Carerj ML; Babbaro M; Pepi M; Chiesa M; Pontone G
    Comput Biol Med; 2023 Feb; 153():106484. PubMed ID: 36584604
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA.
    Muscogiuri G; Chiesa M; Trotta M; Gatti M; Palmisano V; Dell'Aversana S; Baessato F; Cavaliere A; Cicala G; Loffreno A; Rizzon G; Guglielmo M; Baggiano A; Fusini L; Saba L; Andreini D; Pepi M; Rabbat MG; Guaricci AI; De Cecco CN; Colombo G; Pontone G
    Atherosclerosis; 2020 Feb; 294():25-32. PubMed ID: 31945615
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Diagnostic accuracy of 3D deep-learning-based fully automated estimation of patient-level minimum fractional flow reserve from coronary computed tomography angiography.
    Kumamaru KK; Fujimoto S; Otsuka Y; Kawasaki T; Kawaguchi Y; Kato E; Takamura K; Aoshima C; Kamo Y; Kogure Y; Inage H; Daida H; Aoki S
    Eur Heart J Cardiovasc Imaging; 2020 Apr; 21(4):437-445. PubMed ID: 31230076
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Diagnostic performance of deep learning-based vascular extraction and stenosis detection technique for coronary artery disease.
    Chen M; Wang X; Hao G; Cheng X; Ma C; Guo N; Hu S; Tao Q; Yao F; Hu C
    Br J Radiol; 2020 Sep; 93(1113):20191028. PubMed ID: 32101464
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [Deep learning reconstruction algorithm for coronary CT angiography in assessing obstructive coronary artery disease caused by calcified lesions: the clinical application value].
    Xu C; Yi Y; Li YY; Guo YB; Jin ZY; Wang YN
    Zhonghua Yi Xue Za Zhi; 2021 Oct; 101(39):3202-3207. PubMed ID: 34689531
    [No Abstract]   [Full Text] [Related]  

    [Next]    [New Search]
    of 26.