Semantic Scholar Open Access 2017 12833 sitasi

A survey on deep learning in medical image analysis

G. Litjens Thijs Kooi B. Bejnordi A. Setio F. Ciompi +4 lainnya

Lihat Sumber DOI

Abstrak

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks. Concise overviews are provided of studies per application area: neuro, retinal, pulmonary, digital pathology, breast, cardiac, abdominal, musculoskeletal. We end with a summary of the current state-of-the-art, a critical discussion of open challenges and directions for future research.

Topik & Kata Kunci

Computer Science Medicine

Penulis (9)

G. Litjens

Thijs Kooi

B. Bejnordi

A. Setio

F. Ciompi

Mohsen Ghafoorian

J. Laak

B. Ginneken

C. I. Sánchez

Format Sitasi

APA MLA BibTeX

Litjens, G., Kooi, T., Bejnordi, B., Setio, A., Ciompi, F., Ghafoorian, M. et al. (2017). A survey on deep learning in medical image analysis. https://doi.org/10.1016/j.media.2017.07.005

Akses Cepat

Lihat di Sumber doi.org/10.1016/j.media.2017.07.005

Informasi Jurnal

Tahun Terbit: 2017
Bahasa: en
Total Sitasi: 12833×
Sumber Database: Semantic Scholar
DOI: 10.1016/j.media.2017.07.005
Akses: Open Access ✓