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Lutnick B, Ginley B, Govind D, McGarry SD, LaViolette PS, Yacoub R, Jain S, Tomaszewski JE, Jen KY, Sarder P. An integrated iterative annotation technique for easing neural network training in medical image analysis. NAT MACH INTELL 2019; 1:112-119. [PMID: 31187088 PMCID: PMC6557463 DOI: 10.1038/s42256-019-0018-3] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Accepted: 01/07/2019] [Indexed: 01/29/2023]
Abstract
Neural networks promise to bring robust, quantitative analysis to medical fields. However, their adoption is limited by the technicalities of training these networks and the required volume and quality of human-generated annotations. To address this gap in the field of pathology, we have created an intuitive interface for data annotation and the display of neural network predictions within a commonly used digital pathology whole-slide viewer. This strategy used a 'human-in-the-loop' to reduce the annotation burden. We demonstrate that segmentation of human and mouse renal micro compartments is repeatedly improved when humans interact with automatically generated annotations throughout the training process. Finally, to show the adaptability of this technique to other medical imaging fields, we demonstrate its ability to iteratively segment human prostate glands from radiology imaging data.
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Affiliation(s)
- Brendon Lutnick
- Department of Pathology & Anatomical Sciences, SUNY Buffalo, New York, NY, USA
| | - Brandon Ginley
- Department of Pathology & Anatomical Sciences, SUNY Buffalo, New York, NY, USA
| | - Darshana Govind
- Department of Pathology & Anatomical Sciences, SUNY Buffalo, New York, NY, USA
| | - Sean D. McGarry
- Department of Biophysics, Medical College of Wisconsin, Wauwatosa, WI, USA
| | - Peter S. LaViolette
- Department of Radiology and Biomedical Engineering, Medical College of Wisconsin, Wauwatosa, WI, USA
| | - Rabi Yacoub
- Department of Medicine, Nephrology, SUNY Buffalo, New York, NY, USA
| | - Sanjay Jain
- Department of Medicine, Nephrology, Washington University School of Medicine, St Louis, MO, USA
| | - John E. Tomaszewski
- Department of Pathology & Anatomical Sciences, SUNY Buffalo, New York, NY, USA
| | - Kuang-Yu Jen
- Department of Pathology, University of California, Davis Medical Center, Sacramento, CA, USA
| | - Pinaki Sarder
- Department of Pathology & Anatomical Sciences, SUNY Buffalo, New York, NY, USA
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Çelebi S, Burkay Çöteli M. Red and white blood cell classification using Artificial Neural Networks. AIMS BIOENGINEERING 2018. [DOI: 10.3934/bioeng.2018.3.179] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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