Learning Subjective Image Quality Assessment for Transvaginal Ultrasound Scans from Multi-Annotator Labels

Author:

Petashvili Daniel1,Wang Hu1,Deslandes Alison1,Avery Jodie1,Condous George2,Carneiro Gustavo3,Hull Louise1,Chen Hsiang-Ting1

Affiliation:

1. The University of Adelaide,South Australia,Australia

2. University of Sydney,Sydney Medical School Nepean

3. University of Surrey,Centre for Vision, Speech and Signal Processing,UK

Funder

Health

Publisher

IEEE

Reference15 articles.

1. Endometrial biomarkers for the non-invasive diagnosis of endometriosis

2. Complications during set-up procedures for laparoscopy in gynecology: open laparoscopy does not reduce the risk of major complications

3. Routine vs. expert-guided transvaginal ultrasound in the diagnosis of endometriosis: A retrospective review

4. A quantitative grading system for the assessment transvaginal ultrasound image quality;Deslandes

5. Automatic quality assessment for 2d fetal sonographic standard plane based on multi-task learning;Luo;CoRR,2019

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