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2019
Assessment of ASPECTS from CT Scans using Deep Learning
Assessment of ASPECTS from CT Scans using Deep Learning
한국멀티미디어학회
박일우, 양형정, 윤웅 외 4명
논문정보
- Publisher
- 멀티미디어학회논문지
- Issue Date
- 2019-05-01
- Keywords
- -
- Citation
- -
- Source
- -
- Journal Title
- -
- Volume
- 22
- Number
- 5
- Start Page
- 573
- End Page
- 579
- DOI
- ISSN
- 12297771
Abstract
Alberta Stroke Program Early Computed Tomographic Scoring (ASPECTS) is a 10-point CT-scan score designed to quantify early ischemic changes in patients with acute ischemic stroke. However, an assessment of ASPECTS remains a challenge for neuroradiologists in stroke centers. The purpose of this study is to develop an automated ASPECTS scoring system that provides decision-making support by utilizing binary classification with three-dimensional convolutional neural network to analyze CT images. The proposed method consists of three main steps: slice filtering, contrast enhancement and image classification. The experiments show that the obtained results are very promising.
- 전남대학교
- KCI
- 멀티미디어학회논문지
저자 정보
| 이름 | 소속 |
|---|---|
| 박일우 | 의학과 |
| 양형정 | 인공지능융합학과 |
| 윤웅 | 의학과 |