# Breast Ultrasound Image Synthesis using Deep Convolutional Generative Adversarial Networks

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/breast-ultrasound-image-synthesis-using-deep-convolutional-generative/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Tomoyuki Fujioka,M. Mori,Kazunori Kubota,Yuka Kikuchi,Leona Katsuta,Mio Adachi,Goshi Oda,Tsuyoshi Nakagawa,Yoshio Kitazume,Ukihide Tateishi |
| Citations | 48 |
| DOI | 10.3390/diagnostics9040176 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2075-4418/9/4/176/pdf?version=1573035161 |
| OpenAlex ID | https://openalex.org/W2988325738 |
| PMID | 31698748 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Yuka Kikuchi](https://scholariq.org/researchers/yuka-kikuchi/)

## Paper journal

- [Diagnostics](https://scholariq.org/journals/diagnostics/)

## Paper primary topic

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

## Paper topics

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Generative Adversarial Networks and Image Synthesis](https://scholariq.org/topics/generative-adversarial-networks-and-image-synthesis/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.