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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2019
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| Accès en ligne: | https://arxiv.org/abs/1912.07329 |
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| _version_ | 1866913491086999552 |
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| author | Jakhar, Karan Kaur, Avneet Gupta, Meenu |
| author_facet | Jakhar, Karan Kaur, Avneet Gupta, Meenu |
| contents | Computer vision has shown promising results in medical image processing. Pneumothorax is a deadly condition and if not diagnosed and treated at time then it causes death. It can be diagnosed with chest X-ray images. We need an expert and experienced radiologist to predict whether a person is suffering from pneumothorax or not by looking at the chest X-ray images. Everyone does not have access to such a facility. Moreover, in some cases, we need quick diagnoses. So we propose an image segmentation model to predict and give the output a mask that will assist the doctor in taking this crucial decision. Deep Learning has proved their worth in many areas and outperformed man state-of-the-art models. We want to use the power of these deep learning model to solve this problem. We have used U-net [13] architecture with ResNet [17] as a backbone and achieved promising results. U-net [13] performs very well in medical image processing and semantic segmentation. Our problem falls in the semantic segmentation category. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1912_07329 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | Pneumothorax Segmentation: Deep Learning Image Segmentation to predict Pneumothorax Jakhar, Karan Kaur, Avneet Gupta, Meenu Computer Vision and Pattern Recognition Computer vision has shown promising results in medical image processing. Pneumothorax is a deadly condition and if not diagnosed and treated at time then it causes death. It can be diagnosed with chest X-ray images. We need an expert and experienced radiologist to predict whether a person is suffering from pneumothorax or not by looking at the chest X-ray images. Everyone does not have access to such a facility. Moreover, in some cases, we need quick diagnoses. So we propose an image segmentation model to predict and give the output a mask that will assist the doctor in taking this crucial decision. Deep Learning has proved their worth in many areas and outperformed man state-of-the-art models. We want to use the power of these deep learning model to solve this problem. We have used U-net [13] architecture with ResNet [17] as a backbone and achieved promising results. U-net [13] performs very well in medical image processing and semantic segmentation. Our problem falls in the semantic segmentation category. |
| title | Pneumothorax Segmentation: Deep Learning Image Segmentation to predict Pneumothorax |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/1912.07329 |