ArticleMedicine2020
Improving segmentation accuracy of CT kidney cancer images using adaptive active contour model.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Innovative approach for first-trimester fetal organ volume measurements using a Virtual Reality system: The Generation R Next Study.The journal of obstetrics and gynaecology research · 2022Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the present study, we retrospectively analyzed the records of surgical confirmed kidney cancer with renal cell carcinoma pathology in the database of the hospital. We evaluated the significance of cancer size by assessing the outcomes of proposed adaptive active contour model (ACM). The aim of our study was to develop an adaptive ACM method to measure the radiological size of kidney cancer on computed tomography in the hospital patients. This paper proposed a set of medical image processing, applying images provided by the hospital and select the more obvious cases by the doctors, after the first treatment to remove noise image, and the kidney cancer contour would be circled by using the proposed adaptive ACM method. The results showed that the experimental outcome has highly similarity with the medical professional manual contour. The accuracy rate is higher than 99%. We have developed a novel adaptive ACM approach that well combines a knowledge-based system to contour the kidney cancer size in computed tomography imaging to support the clinical decision.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.