{"id":25299918,"url":"https://github.com/jpedrou/brain-tumor-detection","last_synced_at":"2025-10-28T06:30:43.078Z","repository":{"id":246841448,"uuid":"822154517","full_name":"jpedrou/brain-tumor-detection","owner":"jpedrou","description":"This project uses deep learning with CNNs to detect brain tumors in MRI images, aiming for accurate tumor pattern identification.","archived":false,"fork":false,"pushed_at":"2025-06-17T10:49:28.000Z","size":4645,"stargazers_count":5,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-17T11:45:21.447Z","etag":null,"topics":["classification","deep-learning","deep-neural-networks","keras","python","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jpedrou.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-06-30T12:33:51.000Z","updated_at":"2025-06-17T10:49:26.000Z","dependencies_parsed_at":null,"dependency_job_id":"5ee59fb5-edcc-434d-b0c1-0daf90dc1aae","html_url":"https://github.com/jpedrou/brain-tumor-detection","commit_stats":null,"previous_names":["jpedrou/brain-tumor-detection"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jpedrou/brain-tumor-detection","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jpedrou%2Fbrain-tumor-detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jpedrou%2Fbrain-tumor-detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jpedrou%2Fbrain-tumor-detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jpedrou%2Fbrain-tumor-detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jpedrou","download_url":"https://codeload.github.com/jpedrou/brain-tumor-detection/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jpedrou%2Fbrain-tumor-detection/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":281397336,"owners_count":26493908,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-28T02:00:06.022Z","response_time":60,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["classification","deep-learning","deep-neural-networks","keras","python","tensorflow"],"created_at":"2025-02-13T05:35:36.300Z","updated_at":"2025-10-28T06:30:42.693Z","avatar_url":"https://github.com/jpedrou.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align = 'center'\u003e\u003cimg width=150 src = 'reports/A modern brain in a black background in a high quality pixel art style.png'\u003c/p\u003e\n\u003ch1 align = 'center'\u003eBrain Tumor Detection\u003c/h1\u003e\n\nThis repository aims to implement a Convolutional Neural Network (CNN) for brain tumor detection. The project includes a Python-based CNN model trained on a dataset of brain MRI scans to classify images as either tumor-present or tumor-absent. Additionally, a user-friendly interface is provided to allow easy interaction with the trained model. This interface enables users to upload MRI scans and visualize predictions. The data  is from https://www.kaggle.com/datasets/ahmedhamada0/brain-tumor-detection. \n\nThe project serves as a practical demonstration of applying deep learning techniques to medical image analysis, specifically for brain tumor detection, with accessibility in mind through a user-friendly interface.\n\n\n\n**Goal**\n- Implement a CNN for brain tumor detection from MRI images.\n- Integrate a simple and intuitive user interface for interaction.\n\n## Installation\n1. Install dependencies:\n```bash\nconda env create -f environment.yml\n```\n\n2. In the directory where is the file app.py, run:\n```bash\npython app.py\n```\n\n3. Open the index.html in your browser (located in templates folder).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjpedrou%2Fbrain-tumor-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjpedrou%2Fbrain-tumor-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjpedrou%2Fbrain-tumor-detection/lists"}