Notice of Removal: IAT: A Full-Scale IVUS Analysis Toolbox Based on Deep Learning Algorithms for Clinical Diagnosis

Author:

Zhang Wenzhen1ORCID,Cao Yankun2ORCID,Hu Xifeng1ORCID,Mi Jia3ORCID,Zhang Pengfei4ORCID,Mukhopadhyay Subhas Chandra5ORCID,Li Yujun1ORCID,Liu Zhi1ORCID

Affiliation:

1. School of Information Science and Engineering, Shandong University, Qingdao, China

2. School of Software, Shandong University, Jinan, China

3. Department of Special Examination, Shandong Provincial Third Hospital, Jinan, China

4. Department of Cardiology, Qilu Hospital of Shandong University, Jinan, China

5. School of Engineering, Macquarie University, Sydney, NSW, Australia

Funder

Major Scientific and Technological Innovation Project of Shandong Province

Independent Innovation Major Project of Qingdao

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Reference53 articles.

1. American College of Cardiology clinical expert consensus document on standards for acquisition, measurement and reporting of intravascular ultrasound studies (ivus)31When citing this document, the American College of Cardiology would appreciate the following citation format: Mintz GS, Nissen SE, Anderson WD, Bailey SR, Erbel R, Fitzgerald PJ, Pinto FJ, Rosenfield K, Siegel RJ, Tuzcu EM, Yock PG. ACC Clinical Expert Consensus Document on Standards for the acquisition, measurement and reporting of intravascular ultrasound studies: a report of the American College of Cardiology Task Force on Clinical Expert Consensus Documents (Committee to Develop a Clinical Expert Consensus Document on Standards for Acquisition, Measurement and Reporting of Intravascular Ultrasound Studies [IVUS]). J Am Coll Cardiol2001;37:1478–92.33Address for reprints: This document is available on the ACC Website at www.acc.org. Reprints of this document are available for $5.00 each by calling 800-253-4636 (U.S. only) or writing to the Resource Center, American College of Cardiology, Educational Services, 9111 Old Georgetown Road, Bethesda, MD 20814-1699.

2. A Domain Enriched Deep Learning Approach to Classify Atherosclerosis Using Intravascular Ultrasound Imaging

3. A State-of-the-Art Review on Segmentation Algorithms in Intravascular Ultrasound (IVUS) Images

4. Computer-aided diagnosis in medical imaging: Historical review, current status and future potential

5. Statistical shape models for 3D medical image segmentation: A review

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