Microscopy image segmentation tool: Robust image data analysis

被引:9
|
作者
Valmianski, Ilya [1 ]
Monton, Carlos
Schuller, Ivan K.
机构
[1] Univ Calif San Diego, Dept Phys, La Jolla, CA 92093 USA
来源
REVIEW OF SCIENTIFIC INSTRUMENTS | 2014年 / 85卷 / 03期
关键词
POROUS ALUMINA; SILICON; NANOPARTICLES; ARRAYS; SHAPE; FABRICATION; ALGORITHM; FILMS;
D O I
10.1063/1.4866687
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano-and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy. (C) 2014 AIP Publishing LLC.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] A robust and convenient tool for image segmentation.
    Dorn, J. F.
    Boisvert, J.
    Cargnello, M.
    Roux, P.
    Maddox, P. S.
    MOLECULAR BIOLOGY OF THE CELL, 2012, 23
  • [2] Image analysis: In microscopy indispensable tool
    Gharibian, S
    BIOFUTUR, 1997, (169) : A10 - &
  • [3] Realistic Data Enrichment for Robust Image Segmentation in Histopathology
    Cechnicka, Sarah
    Ball, James
    Reynaud, Hadrien
    Arthurs, Callum
    Roufosse, Candice
    Kainz, Bernhard
    DOMAIN ADAPTATION AND REPRESENTATION TRANSFER, DART 2023, 2024, 14293 : 63 - 72
  • [4] Probabilistic Image Diversification to Improve Segmentation in 3D Microscopy Image Data
    Eschweiler, Dennis
    Schock, Justus
    Stegmaier, Johannes
    SIMULATION AND SYNTHESIS IN MEDICAL IMAGING, SASHIMI 2022, 2022, 13570 : 24 - 33
  • [5] Cell Segmentation Proposal Network for Microscopy Image Analysis
    Akram, Saad Ullah
    Kannala, Juho
    Eklund, Lauri
    Heikkila, Janne
    DEEP LEARNING AND DATA LABELING FOR MEDICAL APPLICATIONS, 2016, 10008 : 21 - 29
  • [6] Robust image segmentation technique for rock fragmentation analysis
    Mann, GK
    CIM BULLETIN, 2006, 98 (1091):
  • [7] Robust analysis of feature spaces: Color image segmentation
    Comaniciu, D
    Meer, P
    1997 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, PROCEEDINGS, 1997, : 750 - 755
  • [8] An Image Preprocessing Method for Fingernail Segmentation in Microscopy Image
    Lee, Shih-Hsiung
    Yang, Chu-Sing
    Hou, Ting-Wei
    Yeh, Chien-Hui
    2017 IEEE 2ND INTERNATIONAL CONFERENCE ON SIGNAL AND IMAGE PROCESSING (ICSIP), 2017, : 489 - 493
  • [9] A study of image segmentation based on a robust data clustering method
    Ryu, H
    Miyanaga, Y
    ELECTRONICS AND COMMUNICATIONS IN JAPAN PART III-FUNDAMENTAL ELECTRONIC SCIENCE, 2004, 87 (07): : 27 - 35
  • [10] An Image Segmentation Tool (IST)
    Heric, D
    Potocnik, B
    PROCEEDINGS EC-VIP-MC 2003, VOLS 1 AND 2, 2003, : 483 - 488