Automatic Brain Extraction in Nissl-Stained Histological Sections

被引：0
|
作者：
Smolcic, T. [1 ]
Petkovic, T. [2 ]
Skokic, S. [1 ]
机构：
[1] Univ Zagreb, Sch Med, Zagreb, Croatia
[2] Univ Zagreb, Fac Elect Engn & Comp, Zagreb, Croatia
来源：
2020 43RD INTERNATIONAL CONVENTION ON INFORMATION, COMMUNICATION AND ELECTRONIC TECHNOLOGY (MIPRO 2020) | 2020年
关键词：
brain segmentation; anisotropic diffusion; shape smoothing; histology; FOCAL CEREBRAL-ISCHEMIA; MOUSE-BRAIN; SEGMENTATION;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A simple and robust algorithm for automatic segmentation of Nissl-stained histological brain images is presented. The algorithm preprocesses the input image with anisotropic diffusion filter prior to applying standard binary image manipulations to isolate the brain from the background. Shape smoothing filter is applied to mimic the common practice of human evaluators. The developed code is tested on histological sections of mouse brains and shows good agreement with manual segmentation results.
引用
收藏
页码：283 / 287
页数：5
相关论文
共 50 条
  • [1] An automated mapping method for Nissl-stained mouse brain histologic sections
    Shiffman, Smadar
    Basak, Sayantani
    Kozlowski, Cleopatra
    Fuji, Reina N.
    JOURNAL OF NEUROSCIENCE METHODS, 2018, 308 : 219 - 227
  • [2] Automated Atlas-Based Segmentation of NISSL-Stained Mouse Brain Sections Using Supervised Learning
    Senyukova, O. V.
    Lukin, A. S.
    Vetrov, D. P.
    PROGRAMMING AND COMPUTER SOFTWARE, 2011, 37 (05) : 245 - 251
  • [3] Automatic macroscopic density artefact removal in a Nissl-stained microscopic atlas of whole mouse brain
    Ding, W.
    Li, A.
    Wu, J.
    Yang, Z.
    Meng, Y.
    Wang, S.
    Gong, H.
    JOURNAL OF MICROSCOPY, 2013, 251 (02) : 168 - 177
  • [4] Automated atlas-based segmentation of NISSL-stained mouse brain sections using supervised learning
    O. V. Senyukova
    A. S. Lukin
    D. P. Vetrov
    Programming and Computer Software, 2011, 37 : 245 - 251
  • [5] RESOLVING SINGLE CELLS IN HEAVILY CLUSTERED NISSL-STAINED IMAGES FOR THE ANALYSIS OF BRAIN CYTOARCHITECTURE
    Grisan, Enrico
    Graic, Jean-Marie
    Corain, Livio
    Peruffo, Antonella
    2018 IEEE 15TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2018), 2018, : 427 - 430
  • [6] DISTRIBUTION OF NEUROTENSIN IMMUNOREACTIVITY WITHIN THE HUMAN AMYGDALOID COMPLEX - A COMPARISON WITH ACETYLCHOLINESTERASE-STAINED AND NISSL-STAINED TISSUE-SECTIONS
    BENZING, WC
    MUFSON, EJ
    JENNES, L
    STOPA, EG
    ARMSTRONG, DM
    JOURNAL OF COMPARATIVE NEUROLOGY, 1992, 317 (03) : 283 - 297
  • [7] DEMONSTRATION OF OCULAR DOMINANCE COLUMNS IN NISSL-STAINED SECTIONS OF MONKEY VISUAL-CORTEX FOLLOWING ENUCLEATION
    HASELTINE, EC
    DEBRUYN, EJ
    CASAGRANDE, VA
    BRAIN RESEARCH, 1979, 176 (01) : 153 - 158
  • [8] An automatic nonrigid registration for stained histological sections
    Auer, M
    Regitnig, P
    Holzapfel, GA
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2005, 14 (04) : 475 - 486
  • [9] Machine learning-based segmentation of the rodent hippocampal CA2 area from Nissl-stained sections
    Takeuchi, Yuki
    Yamashiro, Kotaro
    Noguchi, Asako
    Liu, Jiayan
    Mitsui, Shinichi
    Ikegaya, Yuji
    Matsumoto, Nobuyoshi
    FRONTIERS IN NEUROANATOMY, 2023, 17
  • [10] HUMAN COCHLEAR NUCLEUS - COMPARISON OF NISSL-STAINED NEURONS FROM DEAF AND HEARING PATIENTS
    SELDON, HL
    CLARK, GM
    BRAIN RESEARCH, 1991, 551 (1-2) : 185 - 194
12345