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However, there is no reliable method for the recognition, screening, classification, and detection of nodules, and even deep learning-based methods have limitations. In this study, we mainly explored the automatic pre-diagnosis of lung nodules with the aim of accurately identifying nodules in chest CT images, regardless of the benign and malignant nodules, and the insertion path planning of suspected malignant nodules, used for further diagnosis by robotic-based biopsy puncture. The overall process included lung parenchyma segmentation, classification and pre-diagnosis, 3-D reconstruction and path planning, and experimental verification. First, accurate lung parenchyma segmentation in chest CT images was achieved using digital image processing technologies, such as adaptive gray threshold, connected area labeling, and mathematical morphological boundary repair. Multi-feature weight assignment was then adopted to establish a multi-level classification criterion to complete the classification and pre-diagnosis of pulmonary nodules. Next, 3-D reconstruction of lung regions was performed using voxelization, and on its basis, a feasible local optimal insertion path with an insertion point could be found by avoiding sternums and\/or key tissues in terms of the needle-inserting path. Finally, CT images of 900 patients from Lung Image Database Consortium and Image Database Resource Initiative were chosen to verify the validity of pulmonary nodule diagnosis. Our previously designed surgical robotic system and a custom thoracic model were used to validate the effectiveness of the insertion path. This work can not only assist doctors in completing the pre-diagnosis of pulmonary nodules but also provide a reference for clinical biopsy puncture of suspected malignant nodules considered by doctors.<\/jats:p>","DOI":"10.1186\/s12880-023-00973-z","type":"journal-article","created":{"date-parts":[[2023,2,3]],"date-time":"2023-02-03T11:03:14Z","timestamp":1675422194000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Lung nodule pre-diagnosis and insertion path planning for chest CT images"],"prefix":"10.1186","volume":"23","author":[{"given":"Rong-Li","family":"Xie","sequence":"first","affiliation":[]},{"given":"Yao","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yan-Na","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Guang-Biao","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jian","family":"Fei","sequence":"additional","affiliation":[]},{"given":"Zhuang","family":"Fu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,3]]},"reference":[{"key":"973_CR1","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1016\/j.bspc.2018.01.011","volume":"43","author":"J Zhang","year":"2018","unstructured":"Zhang J, Xia Y, Cui H, Zhang Y. 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All human chest CT images were approved by LIDC-IDRI, confirming that informed consent was obtained from all participants or, if participants were under 18\u00a0years of age, from a parent and\/or legal guardian. The formal consent for this type of study was approved by the Academic Ethics Committee of Shanghai Jiao Tong University, Shanghai, China. And the experimental protocols for biopsy puncture using a custom-made thoracic model were approved by the Academic Ethics Committee of Shanghai Jiao Tong University, Shanghai, China. This article does not contain any studies involving human participants or animals performed by any of the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no potential conflicts of interest with respect to the research, authorship, and\/or publication of this article.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"22"}}