2022
DOI: 10.1155/2022/2858845
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Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach

Abstract: Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important tasks for neurologists and radiologists is to detect brain tumors early. Recent claims have been made that computer-aided diagnosis-based systems can diagnose brain tumors by employing magnetic resonance imaging (MRI) as a supporting technology. We propose transfer learning approaches for a deep learning model to detect malignant tumors, such as glioblastoma, using MRI scans in this study. This paper presents a … Show more

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Cited by 41 publications
(23 citation statements)
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“…e study in [29,30] used a DBN model to understand schizophrenia pathology wherein a DBN based deep learning model was used to extract features from brain morphometry data. is helps to investigate its performance discriminating healthy controls from patients suffering from schizophrenia.…”
Section: Exploration Of Educational Reform Taking Online Teaching As ...mentioning
confidence: 99%
“…e study in [29,30] used a DBN model to understand schizophrenia pathology wherein a DBN based deep learning model was used to extract features from brain morphometry data. is helps to investigate its performance discriminating healthy controls from patients suffering from schizophrenia.…”
Section: Exploration Of Educational Reform Taking Online Teaching As ...mentioning
confidence: 99%
“…Khan et al 19 have proposed a system that uses the deep learning model MASK-RCNN for segmentation and pre-trained DenseNet for classification. Using YOLOv5, Shelatkar et al 20 describe a deep learning-based method for classifying and identifying brain tumours. To extract the features, a transfer learning concept is used which is then exposed to selection and classification stages.…”
Section: Literature Surveymentioning
confidence: 99%
“…Performing MRI for research is difficult due to cost burden. Recently, the use of deep learning algorithms in medical imaging is rapidly increasing 50 , 51 . If a model capable of diagnosing tarsal coalition using imaging findings of CT scans is developed, this problem could be improved.…”
Section: Discussionmentioning
confidence: 99%