Abstract
Laparoscopic exploration of the abdominal cavity is routinely performed for the diagnosis, assessment, and staging of peritoneal metastasis (PM). Accurately measuring tumor size during this procedure is crucial for prognosis and treatment planning. As conventional approaches for tumor size measurement rely on subjective manual assessments during or after surgery, they stand to benefit from computer assistance. This study proposes a new method for measuring tumor size in laparoscopic monocular videos. Specifically, we introduce a novel mathematical equation that connects the intrinsic parameters of a monocular camera, the surface area of target and reference objects, and their distances to the camera. Furthermore, we combine this equation with an object segmentation model (Mask2Former) and a depth estimation model (MiDaS), creating an end-to-end framework that automates tumor size measurement in monocular laparoscopic videos. We evaluate the proposed method using a laparoscopy dataset comprising 18 videos depicting 76 tumor biopsies, with tumor size measured by surgeons who are experts in laparoscopic surgery. When estimating the size of the various tumors in this dataset, we obtain a Mean Absolute Error (MAE) of 2.44 mm ± 0.23 mm, demonstrating that the newly proposed method accurately predicts intraoperative tumor size. Our code and the evaluation dataset are publicly available on https://github.com/amiiiirrrr/TSEMLV.
S. A. Mousavi and F. Tozzi—These authors have contributed equally to this work.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Altman, D.G., Bland, J.M.: Measurement in medicine: the analysis of method comparison studies. J. Royal Stat. Soc. Ser. D Stat. 32(3), 307–317 (1983)
Alyami, M., et al.: Pressurised intraperitoneal aerosol chemotherapy: rationale, evidence, and potential indications. Lancet Oncol. 20(7), e368–e377 (2019)
Andaló, F.A., Taubin, G., Goldenstein, S.: Efficient height measurements in single images based on the detection of vanishing points. Comput. Vis. Image Underst. 138, 51–60 (2015)
Birkl, R., Wofk, D., Müller, M.: MiDaS v3. 1–a model zoo for robust monocular relative depth estimation. arXiv preprint arXiv:2307.14460 (2023)
Cheng, B., Misra, I., Schwing, A.G., Kirillov, A., Girdhar, R.: Masked-attention mask transformer for universal image segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1290–1299, June 2022
Criminisi, A., Reid, I., Zisserman, A.: Single view metrology. Int. J. Comput. Vision 40, 123–148 (2000)
Goldstein, O., Segol, O., Gross, S.A., Jacob, H., Siersema, P.D.: Novel device for measuring polyp size: an ex vivo animal study. Gut 67, 1755–1756 (2018)
Harmon, R.L., Sugarbaker, P.H.: Prognostic indicators in peritoneal carcinomatosis from gastrointestinal cancer. In: International Seminars in Surgical Oncology, vol. 2, pp. 1–10. BioMed Central (2005)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2003)
Iakovidis, D.K., Dimas, G., Karargyris, A., Bianchi, F., Ciuti, G., Koulaouzidis, A.: Deep endoscopic visual measurements. IEEE J. Biomed. Health Inform. 23(6), 2211–2219 (2018)
Jacquet, P., Sugarbaker, P.H.: Clinical research methodologies in diagnosis and staging of patients with peritoneal carcinomatosis. In: Peritoneal Carcinomatosis: Principles of Management, pp. 359–374 (1996)
Oka, K., Seki, T., Akatsu, T., Wakabayashi, T., Inui, K., Yoshino, J.: Clinical study using novel endoscopic system for measuring size of gastrointestinal lesion. World J. Gastroenterol. WJG 20(14), 4050 (2014)
Sugarbaker, P.H., Jablonski, K.A.: Prognostic features of 51 colorectal and 130 appendiceal cancer patients with peritoneal carcinomatosis treated by cytoreductive surgery and intraperitoneal chemotherapy. Ann. Surg. 221(2), 124 (1995)
Visentini-Scarzanella, M., et al.: A structured light laser probe for gastrointestinal polyp size measurement: a preliminary comparative study. Endosc. Int. Open 6(05), E602–E609 (2018)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)
Zhang, Z., Han, Y., Zhou, Y., Dai, M.: A novel absolute localization estimation of a target with monocular vision. Optik 124(12), 1218–1223 (2013)
Zhou, M., Bao, G., Geng, Y., Alkandari, B., Li, X.: Polyp detection and radius measurement in small intestine using video capsule endoscopy. In: 2014 7th International Conference on Biomedical Engineering and Informatics, pp. 237–241. IEEE (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2025 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Mousavi, S.A. et al. (2025). A Reference-Based Approach for Tumor Size Estimation in Monocular Laparoscopic Videos. In: Wu, J., Qin, W., Li, C., Kim, B. (eds) Computational Mathematics Modeling in Cancer Analysis. CMMCA 2024. Lecture Notes in Computer Science, vol 15181. Springer, Cham. https://doi.org/10.1007/978-3-031-73360-4_2
Download citation
DOI: https://doi.org/10.1007/978-3-031-73360-4_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-73359-8
Online ISBN: 978-3-031-73360-4
eBook Packages: Computer ScienceComputer Science (R0)