{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/estimation-of-the-volume-of-the-left","title":"Estimation of the volume of the left ventricle from MRI images using deep neural networks","arxiv_id":"1702.03833","date":"2017-02-13","proceeding":null,"authors":["Fangzhou Liao","Xi Chen","Xiaolin Hu","Sen Song"],"abstract":"Segmenting human left ventricle (LV) in magnetic resonance imaging (MRI)\nimages and calculating its volume are important for diagnosing cardiac\ndiseases. In 2016, Kaggle organized a competition to estimate the volume of LV\nfrom MRI images. The dataset consisted of a large number of cases, but only\nprovided systole and diastole volumes as labels. We designed a system based on\nneural networks to solve this problem. It began with a detector combined with a\nneural network classifier for detecting regions of interest (ROIs) containing\nLV chambers. Then a deep neural network named hypercolumns fully convolutional\nnetwork was used to segment LV in ROIs. The 2D segmentation results were\nintegrated across different images to estimate the volume. With ground-truth\nvolume labels, this model was trained end-to-end. To improve the result, an\nadditional dataset with only segmentation label was used. The model was trained\nalternately on these two datasets with different types of teaching signals. We\nalso proposed a variance estimation method for the final prediction. Our\nalgorithm ranked the 4th on the test set in this competition.","url_abs":"http://arxiv.org/abs/1702.03833v1","url_pdf":"http://arxiv.org/pdf/1702.03833v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"estimation-of-the-volume-of-the-left","repo_url":"https://github.com/lfz/Heart-Volume-Estimation","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}