About Me

I am a radiologist at Mayo Clinic. I specialize in imaging diagnosis of abdominal and pelvic organs.

I started research focusing on imaging diagnosis of IgG4-related diseases and renal tumors. Recently, my research has centered on image analysis using programming, deep learning, and machine learning. In particular, I am working on a project to create AI for cancer detection using prostate MR.


Selected Paper

  1. Takahashi N, Kawashima A, Fletcher JG, Chari ST. Renal Involvement in Patients with Autoimmune Pancreatitis: CT and MR Imaging Findings. Radiology. 2007;242(3):791–801. doi: 10.1148/radiol.2423060003 .
  2. Takahashi N, Papachristou GI, Schmit GD, et al. CT findings of walled-off pancreatic necrosis (WOPN): differentiation from pseudocyst and prediction of outcome after endoscopic therapy. Eur Radiol. 2008;18(11):2522–2529. doi: 10.1007/s00330-008-1039-1 .
  3. Chari ST, Takahashi N, Levy MJ, et al. A Diagnostic Strategy to Distinguish Autoimmune Pancreatitis From Pancreatic Cancer. Clinical Gastroenterology and Hepatology. 2009;7(10):1097–1103. doi: 10.1016/j.cgh.2009.04.020 .
  4. Takahashi N, Glockner JF, Hartman RP, et al. Gadolinium Enhanced Magnetic Resonance Urography for Upper Urinary Tract Malignancy. Journal of Urology. 2010;183(4):1330–1336. doi: 10.1016/j.juro.2009.12.031 .
  5. Takahashi N, Vrtiska TJ, Kawashima A, et al. Detectability of Urinary Stones on Virtual Nonenhanced Images Generated at Pyelographic-Phase Dual-Energy CT. Radiology. 2010;256(1):184–190. doi: 10.1148/radiol.10091411 .
  6. Sasiwimonphan K, Takahashi N, Leibovich BC, Carter RE, Atwell TD, Kawashima A. Small (<4 cm) Renal Mass: Differentiation of Angiomyolipoma without Visible Fat from Renal Cell Carcinoma Utilizing MR Imaging. Radiology. 2012;263(1):9. doi: 10.1148/radiol.12111205 .
  7. Takahashi N, Takeuchi M, Sasaguri K, Leng S, Froemming A, Kawashima A. CT negative attenuation pixel distribution and texture analysis for detection of fat in small angiomyolipoma on unenhanced CT. Abdom Radiol. 2016;41(6):1142–1151. doi: 10.1007/s00261-016-0714-y .
  8. Takahashi N, Sugimoto M, Psutka SP, Chen B, Moynagh MR, Carter RE. Validation study of a new semi-automated software program for CT body composition analysis. Abdom Radiol. 2017;42(9):2369–2375. doi: 10.1007/s00261-017-1123-6 .
  9. Cai JC, Nakai H, Kuanar S, et al. Fully Automated Deep Learning Model to Detect Clinically Significant Prostate Cancer at MRI. Radiology. 2024;312(2):e232635. doi: 10.1148/radiol.232635 .

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Contact

E-mail: takahashi.naoki@mayo.edu

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