Semantic Scholar Open Access 2019 1469 sitasi

Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges

M. H. Hesamian W. Jia Xiangjian He Paul J. Kennedy

Lihat Sumber DOI

Abstrak

Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to separate homogeneous areas as the first and critical component of diagnosis and treatment pipeline. In this article, we present a critical appraisal of popular methods that have employed deep-learning techniques for medical image segmentation. Moreover, we summarize the most common challenges incurred and suggest possible solutions.

Topik & Kata Kunci

Computer Science Medicine

Penulis (4)

M. H. Hesamian

W. Jia

Xiangjian He

Paul J. Kennedy

Format Sitasi

APA MLA BibTeX

Hesamian, M.H., Jia, W., He, X., Kennedy, P.J. (2019). Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges. https://doi.org/10.1007/s10278-019-00227-x

Akses Cepat

Lihat di Sumber doi.org/10.1007/s10278-019-00227-x

Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Total Sitasi: 1469×
Sumber Database: Semantic Scholar
DOI: 10.1007/s10278-019-00227-x
Akses: Open Access ✓