Below are the most recent publications written about "Image Processing, Computer-Assisted" by people in Profiles.
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Kesari A, Maurya S, Sheikh MT, Gupta RK, Singh A. Large blood vessel segmentation in quantitative DCE-MRI of brain tumors: A Swin UNETR approach. Magn Reson Imaging. 2025 05; 118:110342.
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Diamandi J, Raimondo C, Alizadeh M, Flanders A, Tjoumakaris S, Gooch MR, Jabbour P, Rosenwasser R, Mouchtouris N. Use of mean apparent propagator (MAP) MRI in patients with acute ischemic stroke: A comparative study with DTI and NODDI. Magn Reson Imaging. 2025 04; 117:110290.
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Jia W, Li H, Ali R, Shanbhogue KP, Masch WR, Aslam A, Harris DT, Reeder SB, Dillman JR, He L. Investigation of ComBat Harmonization on Radiomic and Deep Features from Multi-Center Abdominal MRI Data. J Imaging Inform Med. 2025 Apr; 38(2):1016-1027.
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Buelo CJ, Velikina J, Mao L, Zhao R, Yuan Q, Ghasabeh MA, Ruschke S, Karampinos DC, Harris DT, Mattison RJ, Jeng MR, Pedrosa I, Kamel IR, Vasanawala S, Yokoo T, Reeder SB, Hernando D. Multicenter, multivendor validation of liver quantitative susceptibility mapping in patients with iron overload at 1.5?T and 3?T. Magn Reson Med. 2025 01; 93(1):330-340.
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Kote R, Ravina M, Goyal H, Mohanty D, Gupta R, Shukla AK, Reddy M, Prasanth PN. Role of textural and radiomic analysis parameters in predicting histopathological parameters of the tumor in breast cancer patients. Nucl Med Commun. 2024 Oct 01; 45(10):835-847.
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Jafari R, Kandpal A, Verma R, Aggarwal V, Gupta RK, Singh A. Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values. NMR Biomed. 2024 12; 37(12):e5230.
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Horng H, Scott C, Winham S, Jensen M, Pantalone L, Mankowski W, Kerlikowske K, Vachon CM, Kontos D, Shinohara RT. Multivariate testing and effect size measures for batch effect evaluation in radiomic features. Sci Rep. 2024 06 17; 14(1):13923.
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LaBella D, Khanna O, McBurney-Lin S, Mclean R, Nedelec P, Rashid AS, Tahon NH, Altes T, Baid U, Bhalerao R, Dhemesh Y, Floyd S, Godfrey D, Hilal F, Janas A, Kazerooni A, Kent C, Kirkpatrick J, Kofler F, Leu K, Maleki N, Menze B, Pajot M, Reitman ZJ, Rudie JD, Saluja R, Velichko Y, Wang C, Warman PI, Sollmann N, Diffley D, Nandolia KK, Warren DI, Hussain A, Fehringer JP, Bronstein Y, Deptula L, Stein EG, Taherzadeh M, Portela de Oliveira E, Haughey A, Kontzialis M, Saba L, Turner B, Br??eler MMT, Ansari S, Gkampenis A, Weiss DM, Mansour A, Shawali IH, Yordanov N, Stein JM, Hourani R, Moshebah MY, Abouelatta AM, Rizvi T, Willms K, Martin DC, Okar A, D'Anna G, Taha A, Sharifi Y, Faghani S, Kite D, Pinho M, Haider MA, Alonso-Basanta M, Villanueva-Meyer J, Rauschecker AM, Nada A, Aboian M, Flanders A, Bakas S, Calabrese E. A multi-institutional meningioma MRI dataset for automated multi-sequence image segmentation. Sci Data. 2024 05 15; 11(1):496.
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Yang A, Finkelstein M, Koo C, Doshi AH. Impact of Deep Learning Image Reconstruction Methods on MRI Throughput. Radiol Artif Intell. 2024 05; 6(3):e230181.
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Simchick G, Zhao R, Yuan Q, Ghasabeh MA, Ruschke S, Karampinos DC, Harris DT, do Vale Souza R, Mattison RJ, Jeng MR, Pedrosa I, Kamel IR, Vasanawala S, Yokoo T, Reeder SB, Hernando D. Practical Application of Multivendor MRI-Based R2* Mapping for Liver Iron Quantification at 1.5?T and 3.0?T. J Magn Reson Imaging. 2025 Jan; 61(1):150-165.