PMID- 35711072
OWN - NLM
STAT- MEDLINE
DCOM- 20221024
LR  - 20231002
IS  - 1618-727X (Electronic)
IS  - 0897-1889 (Print)
IS  - 0897-1889 (Linking)
VI  - 35
IP  - 5
DP  - 2022 Oct
TI  - Automatic Brain Tumor Classification via Lion Plus Dragonfly Algorithm.
PG  - 1382-1408
LID - 10.1007/s10278-022-00635-6 [doi]
AB  - Denoising, skull stripping, segmentation, feature extraction, and classification 
      are five important processes in this paper's development of a brain tumor 
      classification model. The brain tumor image will be imposed first using the 
      entropy-based trilateral filter to de-noising and this image is imposed to skull 
      stripping by means of morphological partition and Otsu thresholding. Adaptive 
      contrast limited fuzzy adaptive histogram equalization (CLFAHE) is also used in 
      the segmentation process. The gray-level co-occurrence matrix (GLCM) 
      characteristics are derived from the segmented image. The collected GLCM features 
      are used in a hybrid classifier that combines the neural network (NN) and deep 
      belief network (DBN) ideas. As an innovation, the hidden neurons of the two 
      classifiers are modified ideally to improve the prediction model's accuracy. The 
      hidden neurons are optimized using a unique hybrid optimization technique known 
      as lion with dragonfly separation update (L-DSU), which integrates the approaches 
      from both DA and LA. Finally, the suggested model's performance is compared to 
      that of the standard models concerning certain performance measures.
CI  - (c) 2022. The Author(s) under exclusive licence to Society for Imaging Informatics 
      in Medicine.
FAU - Leena, B
AU  - Leena B
AD  - KGiSL Institute of Technology, Coimbatore, India. leenab643@gmail.com.
FAU - Jayanthi, A N
AU  - Jayanthi AN
AD  - Sri Ramakrishna Institute of Technology, Coimbatore, India.
LA  - eng
PT  - Journal Article
DEP - 20220616
PL  - United States
TA  - J Digit Imaging
JT  - Journal of digital imaging
JID - 9100529
SB  - IM
MH  - Algorithms
MH  - *Brain Neoplasms/diagnostic imaging/pathology
MH  - Fuzzy Logic
MH  - Image Processing, Computer-Assisted/methods
PMC - PMC9582188
OTO - NOTNLM
OT  - Brain tumor
OT  - CLAFAHE
OT  - DBN and NN
OT  - GLCM
OT  - L-DSU
OT  - Otsu thresholding and morphological segmentation
EDAT- 2022/06/18 06:00
MHDA- 2022/10/22 06:00
PMCR- 2023/10/01
CRDT- 2022/06/17 00:27
PHST- 2021/10/09 00:00 [received]
PHST- 2022/04/09 00:00 [accepted]
PHST- 2022/04/01 00:00 [revised]
PHST- 2022/06/18 06:00 [pubmed]
PHST- 2022/10/22 06:00 [medline]
PHST- 2022/06/17 00:27 [entrez]
PHST- 2023/10/01 00:00 [pmc-release]
AID - 10.1007/s10278-022-00635-6 [pii]
AID - 635 [pii]
AID - 10.1007/s10278-022-00635-6 [doi]
PST - ppublish
SO  - J Digit Imaging. 2022 Oct;35(5):1382-1408. doi: 10.1007/s10278-022-00635-6. Epub 
      2022 Jun 16.