ReviewFrontiers in surgery2025
Vision techniques for anatomical structures in laparoscopic surgery: a comprehensive review.
Review in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
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0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Laparoscopic surgery is the method of choice for numerous surgical procedures, while it confronts a lot of challenges. Computer vision exerts a vital role in addressing these challenges and has become a research hotspot, especially in the classification, segmentation, and target detection of abdominal anatomical structures. This study presents a comprehensive review of the last decade of research in this area. At first, a categorized overview of the core subtasks is presented regarding their relevance and applicability to real-world medical scenarios. Second, the dataset used in the experimental validation is statistically analyzed. Subsequently, the technical approaches and trends of classification, segmentation, and target detection tasks are explored in detail, highlighting their advantages, limitations, and practical implications. Additionally, evaluation methods for the three types of tasks are discussed. Finally, gaps in current research are identified. Meanwhile, the great potential for development in this area is emphasized.
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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.