Automated segmentation of lung, liver, and liver tumors from Tc‐99m MAA SPECT/CT images for Y‐90 radioembolization using convolutional neural networks-Reference-Cited by-同舟云学术

Automated segmentation of lung, liver, and liver tumors from Tc‐99m MAA SPECT/CT images for Y‐90 radioembolization using convolutional neural networks

Published:2021-10-31 Issue:12 Volume:48 Page:7877-7890
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Medical Physics

Author:

Chaichana Anucha¹,Frey Eric C.²³,Teyateeti Ajalaya⁴,Rhoongsittichai Kijja⁴,Tocharoenchai Chiraporn¹,Pusuwan Pawana⁴,Jangpatarapongsa Kulachart⁵

Affiliation:

1. Department of Radiological Technology, Faculty of Medical Technology Mahidol University Bangkok 10700 Thailand

2. Johns Hopkins School of Medicine Johns Hopkins University Baltimore Maryland 21218 USA

3. Radiopharmaceutical Imaging and Dosimetry, LLC Lutherville Maryland 21093 USA

4. Department of Radiology, Faculty of Medicine Siriraj Hospital Mahidol University Bangkok 10700 Thailand

5. Center for Research and Innovation, Faculty of Medical Technology Mahidol University Bangkok 10700 Thailand

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15303

Reference41 articles.

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2. Yttrium-90 Microspheres: Radiation Therapy for Unresectable Liver Cancer

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4. Yttrium-90 hepatic radioembolization: clinical review and current techniques in interventional radiology and personalized dosimetry

5. Radiation Segmentectomy versus TACE Combined with Microwave Ablation for Unresectable Solitary Hepatocellular Carcinoma Up to 3 cm: A Propensity Score Matching Study

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