A Bounding-Box Regression Model for Colorectal Tumor Detection in CT Images Via Two Contrary Networks-Reference-Cited by-同舟云学术

A Bounding-Box Regression Model for Colorectal Tumor Detection in CT Images Via Two Contrary Networks

Published:2022-07-11 Issue: Volume: Page:
ISSN:
Container-title:2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Kim YongSoo¹,Park Seungbin²,Kim Hannah³,Kim Seung-seob⁴,Lim Joon Seok⁴,Kim Sungwon⁴,Choi Kihwan⁵,Seo Hyunseok¹

Affiliation:

1. KIST School, Korea University of Science and Technology,Division of Bio-Medical Science &Technology,Seoul,Republic of Korea

2. Weldon School of Biomedical Engineering, Purdue University,West Lafayette,IN,USA,47907

3. Imagoworks Inc.,Seoul,Republic of Korea,06611

4. Research Institute of Radiological Science, Yonsei University College of Medicine,Severance Hospital,Department of Radiology,Seodaemun-gu,Seoul,South Korea,03722

5. Korea Institute of Science and Technology,Center for bionics, Biomedical Resarch Division,Seoul,Republic of Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871285.pdf?arnumber=9871285

Reference22 articles.

1. Clinical, Pathology, Genetic, and Molecular Features of Colorectal Tumors in Adolescents and Adults 25 Years or Younger

2. Quality of life and symptom attribution in long-term colon cancer survivors

3. Impact of Patient Age on Molecular Alterations of Left-Sided Colorectal Tumors

4. Colonic Polyp Classification with Convolutional Neural Networks

5. Automatic Detection and Classification of Colorectal Polyps by Transferring Low-Level CNN Features From Nonmedical Domain

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