Detailed Information on Publication Record
2015
Performance and Sensitivity Evaluation of 3-D Spot Detection Methods in Confocal Microscopy
ŠTĚPKA, Karel, Pavel MATULA, Petr MATULA, Stefan WOERZ, Karl ROHR et. al.Basic information
Original name
Performance and Sensitivity Evaluation of 3-D Spot Detection Methods in Confocal Microscopy
Authors
ŠTĚPKA, Karel (203 Czech Republic, guarantor, belonging to the institution), Pavel MATULA (203 Czech Republic, belonging to the institution), Petr MATULA (203 Czech Republic, belonging to the institution), Stefan WOERZ (276 Germany), Karl ROHR (276 Germany) and Michal KOZUBEK (203 Czech Republic, belonging to the institution)
Edition
Cytometry Part A, John Wiley & Sons, 2015, 1552-4922
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
Impact factor
Impact factor: 3.181
RIV identification code
RIV/00216224:14330/15:00080577
Organization unit
Faculty of Informatics
UT WoS
000358643200011
Keywords in English
fluorescence microscopy; 3D imaging; diffraction-limited spot detection; parameter sensitivity
Tags
Tags
International impact, Reviewed
Změněno: 9/2/2022 09:19, doc. RNDr. Pavel Matula, Ph.D.
Abstract
V originále
Reliable 3D detection of diffraction-limited spots in fluorescence microscopy images is an important task in subcellular observation. Generally, fluorescence microscopy images are heavily degraded by noise and non-specifically stained background, making reliable detection a challenging task. In this work, we have studied the performance and parameter sensitivity of eight recent methods for 3D spot detection. The study is based on both 3D synthetic image data and 3D real confocal microscopy images. The synthetic images were generated using a simulator modeling the complete imaging setup, including the optical path as well as the image acquisition process. We studied the detection performance and parameter sensitivity under different noise levels and under the influence of uneven background signal. To evaluate the parameter sensitivity, we propose a novel measure based on the gradient magnitude of the F1 score. We measured the success rate of the individual methods for different types of the image data and found that the type of image degradation is an important factor. Using the F1 score and the newly proposed sensitivity measure, we found that the parameter sensitivity is not necessarily proportional to the success rate of a method. This also provided an explanation why the best performing method for synthetic data was outperformed by other methods when applied to the real microscopy images. On the basis of the results obtained, we conclude with the recommendation of the HDome method for data with relatively low variations in quality, or the Sorokin method for image sets in which the quality varies more. We also provide alternative recommendations for high-quality images, and for situations in which detailed parameter tuning might be deemed expensive.
Links
| GBP302/12/G157, research and development project |
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| MUNI/A/1159/2014, interní kód MU |
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