RETRACTED: A novel approach for brain tumor detection by self-organizing map (SOM) using adaptive network based fuzzy inference system (ANFIS) for robotic systems
International Journal of Intelligent Unmanned Systems
ISSN: 2049-6427
Article publication date: 1 February 2021
Issue publication date: 7 January 2022
Retraction notice
The publishers of International Journal of Intelligent Unmanned Systems wish to retract the article Baalamurugan, K.M., Singh, P. and Ramalingam, V. (2022), “A novel approach for brain tumor detection by self-organizing map (SOM) using adaptive network based fuzzy inference system (ANFIS) for robotic systems”, International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 98-116. https://doi.org/10.1108/IJIUS-08-2020-0038
An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald’s publishing ethics and the COPE guidelines on retractions.
The authors of this paper would like to note that they do not agree with the content of this notice.
The publishers of the journal sincerely apologize to the readers.
Abstract
Purpose
One of the foremost research disciplines in medical image processing is to identify tumors, which is a challenging task practicing traditional methods. To overcome this, various research studies have been done effectively.
Design/methodology/approach
Medical image processing is evolving swiftly with modern technologies being developed every day. The advanced technologies improve medical fields in diagnosing diseases at the more advanced stages and serve to provide proper treatment.
Findings
Either the mass growth or abnormal growth concerning the cells in the brain is called a brain tumor.
Originality/value
The brain tumor can be categorized into two significant varieties, non-cancerous and cancerous. The carcinogenic tumors or cancerous is termed as malignant and non-carcinogenic tumors are termed benign tumors. If the cells in the tumor are healthy then it is a benign tumor, whereas, the abnormal growth or the uncontrollable growth of the cell is indicated as malignant. To find the tumor the magnetic resonance imaging (MRI) is carried out which is a tiresome and monotonous task done by a radiologist. In-order to diagnosis the brain tumor at the initial stage effectively with improved accuracy, the computer-aided robotic research technology is incorporated. There are numerous segmentation procedures, which help in identifying tumor cells from MRI images. It is necessary to select a proper segmentation mechanism to detect brain tumors effectively that can be aided with robotic systems. This research paper focuses on self-organizing map (SOM) by applying the adaptive network-based fuzzy inference system (ANFIS). The execution measures are determined to employ the confusion matrix, accuracy, sensitivity, and furthermore, specificity. The results achieved conclusively explicate that the proposed model presents more reliable outcomes when compared to existing techniques.
Keywords
Citation
Baalamurugan, K.M., Singh, P. and Ramalingam, V. (2022), "RETRACTED: A novel approach for brain tumor detection by self-organizing map (SOM) using adaptive network based fuzzy inference system (ANFIS) for robotic systems", International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 98-116. https://doi.org/10.1108/IJIUS-08-2020-0038
Publisher
:Emerald Publishing Limited
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