{"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/evaluate-the-malignancy-of-pulmonary-nodules","title":"Evaluate the Malignancy of Pulmonary Nodules Using the 3D Deep Leaky Noisy-or Network","arxiv_id":"1711.08324","date":"2017-11-22","proceeding":null,"authors":["Fangzhou Liao","Ming Liang","Zhe Li","Xiaolin Hu","Sen Song"],"abstract":"Automatic diagnosing lung cancer from Computed Tomography (CT) scans involves\ntwo steps: detect all suspicious lesions (pulmonary nodules) and evaluate the\nwhole-lung/pulmonary malignancy. Currently, there are many studies about the\nfirst step, but few about the second step. Since the existence of nodule does\nnot definitely indicate cancer, and the morphology of nodule has a complicated\nrelationship with cancer, the diagnosis of lung cancer demands careful\ninvestigations on every suspicious nodule and integration of information of all\nnodules. We propose a 3D deep neural network to solve this problem. The model\nconsists of two modules. The first one is a 3D region proposal network for\nnodule detection, which outputs all suspicious nodules for a subject. The\nsecond one selects the top five nodules based on the detection confidence,\nevaluates their cancer probabilities and combines them with a leaky noisy-or\ngate to obtain the probability of lung cancer for the subject. The two modules\nshare the same backbone network, a modified U-net. The over-fitting caused by\nthe shortage of training data is alleviated by training the two modules\nalternately. The proposed model won the first place in the Data Science Bowl\n2017 competition. The code has been made publicly available.","url_abs":"http://arxiv.org/abs/1711.08324v1","url_pdf":"http://arxiv.org/pdf/1711.08324v1.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":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/lfz/DSB2017","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/Hydron063/Rage","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/Karna4621/dsb_new","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/Lingfeng158/DSBSeperate","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/MichaelMedvedskiy/Neuro_add_learning","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/MichaelMedvedskiy/Neuro_least_changes","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/MichaelMedvedskiy/lung_cancer_modified","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/Nariyiel/DSB2017","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/dronaka/DSB2017","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/hxyshare/lungcancerclassifier","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"evaluate-the-malignancy-of-pulmonary-nodules","repo_url":"https://github.com/xiuchaos/lungCT","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"computed-tomography-ct","task_name":"Computed Tomography (CT)"},{"task_slug":"region-proposal","task_name":"Region Proposal"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1711.08324","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1711.08324"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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