Development and evaluation of an integrated liver nodule diagnostic method by combining the liver segment division and lesion localization/classification models for enhanced focal liver lesion detection-Reference-Cited by-同舟云学术

Development and evaluation of an integrated liver nodule diagnostic method by combining the liver segment division and lesion localization/classification models for enhanced focal liver lesion detection

Published:2023-11-02 Issue: Volume: Page:
ISSN:1865-0333
Container-title:Radiological Physics and Technology
language:en
Short-container-title:Radiol Phys Technol

Author:

Takenaga Tomomi^ORCID,Hanaoka Shouhei^ORCID,Nomura Yukihiro^ORCID,Nakao Takahiro^ORCID,Shibata Hisaichi^ORCID,Miki Soichiro^ORCID,Yoshikawa Takeharu^ORCID,Hayashi Naoto^ORCID,Abe Osamu^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine,Radiation

Link

https://link.springer.com/content/pdf/10.1007/s12194-023-00753-y.pdf

Reference10 articles.

1. Akai H, Kiryu S, Matsuda I, Satou J, Takao H, Tajima T, et al. Detection of hepatocellular carcinoma by Gd-EOB-DTPA-enhanced liver MRI: comparison with triple phase 64 detector row helical CT. Eur J Radiol. 2011;80(2):310–5.

2. Berger-Kulemann V, Schima W, Baroud S, Koelblinger C, Kaczirek K, Gruenberger T, et al. Gadoxetic acid-enhanced 3.0 T MR imaging versus multidetector-row CT in the detection of colorectal metastases in fatty liver using intraoperative ultrasound and histopathology as a standard of reference. Eur J Surg Oncol. 2012;38(8):670–6.

3. Clavien PA, Petrowsky H, DeOliveira ML, Graf R. Strategies for safer liver surgery and partial liver transplantation. N Engl J Med. 2007;356(15):1545–59.

4. Le DC, Chansangrat J, Keeratibharat N, Horkaew P. Functional segmentation for preoperative liver resection based on hepatic vascular networks. IEEE Access. 2021;9:15485–98.

5. Tian Y, Xue F, Lambo R, He J, An C, Xie Y, et al. Fully-automated functional region annotation of liver via a 2.5D class-aware deep neural network with spatial adaptation. Comp Methods Prog Biomed. 2021;200:105818.