scholarly journals MRI Image Based Relatable Pixel Extraction with Image Segmentation for Brain Tumor Cell Detection Using Deep Learning Model

2021 ◽  
Vol 7 (3) ◽  
pp. 31-37
Author(s):  
Rajeshwari Dharavath ◽  
Kattula Shyamala
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Brain Tumor ◽  
Tumor Cell ◽  
Learning Model ◽  
Cell Detection ◽  
Tumor Cell Detection ◽  
Brain Tumor Cell ◽  
Deep Learning Model ◽  
Mri Image

scholarly journals A Deep Learning Model Based on Concatenation Approach for the Diagnosis of Brain Tumor

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 55135-55144 ◽  
Author(s):  
Neelum Noreen ◽  
Sellappan Palaniappan ◽  
Abdul Qayyum ◽  
Iftikhar Ahmad ◽  
Muhammad Imran ◽  
...  
Keyword(s):  
Deep Learning ◽  
Brain Tumor ◽  
Learning Model ◽  
Model Based ◽  
Deep Learning Model

scholarly journals Classification of Knee Osteoarthritis Severity Using Modified Masks to Preprocess X-ray Images in a Deep Learning Model

2021 ◽  
Author(s):  
Ching-Chung Yang
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Knee Osteoarthritis ◽  
Object Detection ◽  
Image Classification ◽  
Learning Model ◽  
X Ray ◽  
Medical Image Classification ◽  
Deep Learning Model

We propose a concise approach to facilitate the deep learning model for medical image classification of knee osteoarthritis severity. The characteristics of the input X-ray images are sharpened by a modified 5×5 mask before training and testing in this work. We compare the inference accuracies of two experiments using the same architecture with images sharpened and not sharpened respectively. And we find it tangible that the former performs much better than the latter. This technique could also be helpful when applied onto the edge devices for object detection and image segmentation.

scholarly journals Application of Machine Learning and Deep Learning Methods for Brain Tumor Identification and Classification

2020 ◽  
Vol 8 (6) ◽  
pp. 2886-2891
Keyword(s):  
Machine Learning ◽  
Image Segmentation ◽  
Deep Learning ◽  
Brain Tumor ◽  
Brain Mri ◽  
Tumor Segmentation ◽  
Survival Ratio ◽  
Reliable Technique ◽  
Tumor Identification ◽  
Mri Image

In the area of medical imaging technology, advances in Artificial intelligence (AI) delivers promising solutions with higher accuracy. For healthcare solutions, medical images provides a systematic way for diagnosis the diseases earlier and make treatments more effective. Machine learning and deep learning are rapidly grown fields of AI that may apply to many domains including image processing, speech recognition and text understanding. As MRI image segmentation is a key task for identification of brain anomalies, a fast and reliable technique is essential for increasing the survival ratio of affected patients. Manual segmentation of the brain MRI image involves more time and it may subject to inaccuracies. Hence, AI approaches and algorithms have been developed for tumor segmentation. This paper contains the detailed study of the available methods of machine learning and deep learning for brain tumor identification and classification through MRI image segmentation. It discusses and summarizes the methodologies and its results available for classification of brain tumor.

scholarly journals A deep learning model integrating FCNNs and CRFs for brain tumor segmentation

2018 ◽  
Vol 43 ◽  
pp. 98-111 ◽  
Author(s):  
Xiaomei Zhao ◽  
Yihong Wu ◽  
Guidong Song ◽  
Zhenye Li ◽  
Yazhuo Zhang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Brain Tumor ◽  
Learning Model ◽  
Tumor Segmentation ◽  
Brain Tumor Segmentation ◽  
Deep Learning Model
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