Hello World Deep Learning in Medical Imaging.
There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries...
| Publicado en: | Journal of Digital Imaging Vol. 31; no. 3; pp. 283 - 290 |
|---|---|
| Autores principales: | , , , , |
| Formato: | computer program diagnostic images tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2018
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=129685405&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 129685405 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2018 vid: 31 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 129685405 129685405 129685405 10.1007/s10278-018-0079-6 129685405 ppf: 283 ppct: 7 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Hello World Deep Learning in Medical Imaging. aug: au: Lakhani, Paras Gray, Daniel L. Pett, Carl R. Nagy, Paul Shih, George affil: Department of Radiology, Sidney Kimmel Jefferson Medical College, Thomas Jefferson University Hospital, 19107, Philadelphia, PA, USA sug: subj: Diagnostic Imaging Machine Learning Neural Networks (Computer) Radiographic Image Interpretation, Computer-Assisted ab: There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects. pubtype: Academic Journal doctype: computer program diagnostic images tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|