Automatic endosomal structure detection and localization in fluorescence microscopic images
Automatic endosomal structure detection and localization in fluorescence microscopic images
This paper proposes a modified spatially-constrained similarity measure (mSCSM) method for endosomal structure detection and localization under the bag-of-words (BoW) framework. To our best knowledge, the proposed mSCSM is the first method for fully automatic detection and localization of complex subcellular compartments like endosomes. Essentially, a new similarity score and a novel two-stage output control scheme are proposed for localization by extracting discriminative information within a group of query images. Compared with the original SCSM which is formulated for instance localization, the proposed mSCSM can address category based localization problems. The preliminary experimental results show the proposed mSCSM can correctly detect and localize 79.17% of the existing endosomal structures in the microscopic images of human myeloid endothelial cells.
bag-of-words (BoW), endosomal structures, histogram intersection, spatially-constrained similarity measure (SCSM)
Lin, Dongyun
c435a10b-1607-4bcb-a9df-1ad4bcfc02c9
Lin, Zhiping
9b046adc-5fd0-4f26-a722-4e72598ecd9f
Velmurugan, Ramraj
4f2d41cd-90eb-4f61-b5e0-df6308726d28
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
25 September 2017
Lin, Dongyun
c435a10b-1607-4bcb-a9df-1ad4bcfc02c9
Lin, Zhiping
9b046adc-5fd0-4f26-a722-4e72598ecd9f
Velmurugan, Ramraj
4f2d41cd-90eb-4f61-b5e0-df6308726d28
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
Lin, Dongyun, Lin, Zhiping, Velmurugan, Ramraj and Ober, Raimund J.
(2017)
Automatic endosomal structure detection and localization in fluorescence microscopic images.
In IEEE International Symposium on Circuits and Systems: From Dreams to Innovation, ISCAS 2017 - Conference Proceedings.
IEEE..
(doi:10.1109/ISCAS.2017.8050242).
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper proposes a modified spatially-constrained similarity measure (mSCSM) method for endosomal structure detection and localization under the bag-of-words (BoW) framework. To our best knowledge, the proposed mSCSM is the first method for fully automatic detection and localization of complex subcellular compartments like endosomes. Essentially, a new similarity score and a novel two-stage output control scheme are proposed for localization by extracting discriminative information within a group of query images. Compared with the original SCSM which is formulated for instance localization, the proposed mSCSM can address category based localization problems. The preliminary experimental results show the proposed mSCSM can correctly detect and localize 79.17% of the existing endosomal structures in the microscopic images of human myeloid endothelial cells.
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Published date: 25 September 2017
Venue - Dates:
50th IEEE International Symposium on Circuits and Systems, ISCAS 2017, , Baltimore, United States, 2017-05-28 - 2017-05-31
Keywords:
bag-of-words (BoW), endosomal structures, histogram intersection, spatially-constrained similarity measure (SCSM)
Identifiers
Local EPrints ID: 423676
URI: http://eprints.soton.ac.uk/id/eprint/423676
PURE UUID: 7a38a20c-a4f7-4333-88de-fea01186364d
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Date deposited: 27 Sep 2018 16:30
Last modified: 18 Mar 2024 03:48
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Contributors
Author:
Dongyun Lin
Author:
Zhiping Lin
Author:
Ramraj Velmurugan
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