Exploring synthetic datasets for computer-aided detection: a case study using phantom scan data for enhanced lung nodule false positive reduction-Reference-Cited by-同舟云学术

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Exploring synthetic datasets for computer-aided detection: a case study using phantom scan data for enhanced lung nodule false positive reduction

Published:2024-08-07 Issue:04 Volume:11 Page:
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Farhangi Mohammad Mehdi¹,Maynord Michael¹,Fermüller Cornelia²,Aloimonos Yiannis²,Sahiner Berkman¹,Petrick Nicholas¹

Affiliation:

1. FDA, CDRH, OSEL, Division of Imaging, Diagnostics, and Software Reliability, Silver Spring, Maryland, United States

2. University of Maryland, Iribe Center for Computer Science and Engineering, Computer Science Department, College Park, Maryland, United States

Publisher

SPIE-Intl Soc Optical Eng

Reference24 articles.

1. Generative adversarial network in medical imaging: A review

2. FocalMix: Semi-Supervised Learning for 3D Medical Image Detection

3. Generating and Evaluating Synthetic UK Primary Care Data: Preserving Data Utility & Patient Privacy

4. A new, open-source, multi-modality digital breast phantom

5. Evaluation of Digital Breast Tomosynthesis as Replacement of Full-Field Digital Mammography Using an In Silico Imaging Trial

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