Výsledky vyhledávání - "Rupasinghe, Mark"

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A 61-year-old woman with jejunal lymphatic malformation visualized on computed tomography: a case report.

Autor: Rupasinghe, Mark¹ (AUTHOR), Houshyar, Roozbeh¹ (AUTHOR) rhoushya@hs.uci.edu, Chahine, Chantal¹ (AUTHOR), Bui, Thanh-Lan¹ (AUTHOR), Glavis-Bloom, Justin¹ (AUTHOR), Cheng, Caleb² (AUTHOR), Tseng, Jill³ (AUTHOR)

Publikováno v: Journal of Medical Case Reports. 5/27/2021, Vol. 15 Issue 1, p1-5. 5p.

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Prostate minimally invasive procedures: complications and normal vs. abnormal findings on multiparametric magnetic resonance imaging (mpMRI)

Autor: Bui, Thanh-Lan, Glavis-Bloom, Justin, Chahine, Chantal, Mehta, Raj, Wolfe, Taylor, Bhatter, Param, Rupasinghe, Mark, Carbone, Joseph, Haider, Masoom A, Giganti, Francesco, Giona, Simone, Oto, Aytekin, Lee, Grace, Houshyar, Roozbeh

Publikováno v: Abdominal radiology (New York), vol 46, iss 9

Minimally invasive alternatives to traditional prostate surgery are increasingly utilized to treat benign prostatic hyperplasia and localized prostate cancer in select patients. Advantages of these treatments over prostatectomy include lower risk of

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______325::54325f33a9448b2de75648ffbbb78181
https://escholarship.org/uc/item/2qr3n8rc

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Prostate minimally invasive procedures: complications and normal vs. abnormal findings on multiparametric magnetic resonance imaging (mpMRI).

Autor: Bui TL; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA., Glavis-Bloom J; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA., Chahine C; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA., Mehta R; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA., Wolfe T; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA., Bhatter P; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA., Rupasinghe M; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA., Carbone J; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA., Haider MA; Joint Department of Medical Imaging, Sinai Health System, University Health Network, University of Toronto, Toronto, ON, Canada., Giganti F; Department of Radiology, University College London Hospital NHS Foundation Trust, London, UK.; Division of Surgery & Interventional Science, University College London, London, UK., Giona S; Department of Urology, Frimley Park Hospital, Frimley, Camberley, UK., Oto A; Department of Radiology, University of Chicago, Chicago, IL, USA., Lee G; Department of Radiology, University of Chicago, Chicago, IL, USA., Houshyar R; Department of Radiological Sciences, University of California, Irvine, Orange, CA, 92868-3201, USA. rhoushya@hs.uci.edu.; Department of Radiological Sciences, University of California, Irvine, Bldg. 1 Route 140, Orange, CA, 92868-3201, USA. rhoushya@hs.uci.edu.

Publikováno v: Abdominal radiology (New York) [Abdom Radiol (NY)] 2021 Sep; Vol. 46 (9), pp. 4388-4400. Date of Electronic Publication: 2021 May 11.

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Segmentation of the Prostate Transition Zone and Peripheral Zone on MR Images with Deep Learning.

Autor: Bardis M; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.)., Houshyar R; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.)., Chantaduly C; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.)., Tran-Harding K; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.)., Ushinsky A; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.)., Chahine C; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.)., Rupasinghe M; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.)., Chow D; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.)., Chang P; From the Department of Radiological Sciences, University of California, Irvine, 101 The City Drive South, Building 55, Suite 201, Orange, CA 92868 (M.B., R.H., K.T.H., C. Chahine, M.R.); Center for Artificial Intelligence in Diagnostic Medicine, University of California, Irvine, Irvine, Calif (C. Chantaduly, D.C., P.C.); and Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (A.U.).

Publikováno v: Radiology. Imaging cancer [Radiol Imaging Cancer] 2021 May; Vol. 3 (3), pp. e200024.

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