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Automatic detection of regions in spinach canopies responding to soil moisture deficit using combined visible and thermal imagery
(
Public Library of Science
, 2014 , Article)
Thermal imaging has been used in the past for remote detection of regions of canopy showing symptoms of stress, including water deficit stress. Stress indices derived from thermal images have been used as an indicator of ...
Automatic detection of diseased tomato plants using thermal and stereo visible light images
(
Public Library of Science
, 2015 , Article)
Accurate and timely detection of plant diseases can help mitigate the worldwide losses experienced by the horticulture and agriculture industries each year. Thermal imaging provides a fast and non-destructive way of scanning ...
Cell phenotyping in multi-tag fluorescent bioimages
(
Elsevier B.V.
, 2014 , Article)
Multi-tag bioimaging systems have recently emerged as powerful tools which provide spatiotemporal localization of several different proteins in the same tissue specimen. The analysis of such multivariate bioimages requires ...
Robust normalization protocols for multiplexed fluorescence bioimage analysis
(
BioMed Central
, 2016 , Article)
The study of mapping and interaction of co-localized proteins at a sub-cellular level is
important for understanding complex biological phenomena. One of the recent
techniques to map co-localized proteins is to use the ...
Handcrafted features with convolutional neural networks for detection of tumor cells in histology images
(
IEEE Computer Society
, 2016 , Conference Paper)
Detection of tumor nuclei in cancer histology images requires sophisticated techniques due to the irregular shape, size and chromatin texture of the tumor nuclei. Some very recently proposed methods employ deep convolutional ...
Stain deconvolution of histology images via independent component analysis in the wavelet domain
(
IEEE Computer Society
, 2016 , Conference Paper)
With the ubiquity of digital slide scanners, histology image analysis is rapidly emerging as an active area of research. Several histology image analysis algorithms such as those for mitotic cell detection, nuclei segmentation ...
Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images
(
Institute of Electrical and Electronics Engineers Inc.
, 2016 , Article)
Detection and classification of cell nuclei in histopathology images of cancerous tissue stained with the standard hematoxylin and eosin stain is a challenging task due to cellular heterogeneity. Deep learning approaches ...