A multiresolution deep learning framework for automated annotation of reflectance confocal microscopy images Conference Paper

  


Authors: Kose, K.; Bozkurt, A.; Alessi-Fox, C.; Gill, M.; Brooks, D. H.; Dy, J. G.; Rajadhyaksha, M.
Title: A multiresolution deep learning framework for automated annotation of reflectance confocal microscopy images
Conference Title: 2018 OSA Biophotonics Congress: Biomedical Optics
Abstract: Morphological tissue patterns in RCM images are critical in diagnosis of melanocytic lesions. We present a multiresolution deep learning framework that can automatically annotate RCM images for these diagnostic patterns with high sensitivity and specificity. © OSA 2018.
Keywords: reflectance confocal microscopies; high sensitivity; melanocytic lesion; learning frameworks; deep learning; image annotation; multi resolutions
Journal Title OSA Technical Digest
Conference Dates: 2018 Apr 3-6
Conference Location: Hollywood, FL
ISBN: 978-1-943580-41-5
Publisher: Optical Society of America  
Date Published: 2018-01-01
Start Page: MTh2A.1
Language: English
DOI: 10.1364/MICROSCOPY.2018.MTh2A.1
PROVIDER: scopus
DOI/URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047943282&doi=10.1364%2fMICROSCOPY.2018.MTh2A.1&partnerID=40&md5=bcb90534bebaf5c6d25ee5c325b4b622
Notes: Conference Paper -- Export Date: 2 July 2018 -- Source: Scopus
Altmetric
What is Altmetric?
Citation Impact
What is Dimensions Citation Badge?
BMJ Impact Analytics
MSK Authors
  1. Milind Rajadhyaksha
    222 Rajadhyaksha
  2. Kivanc Kose
    81 Kose
Related MSK Work