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000308544 1001_ $$aRueckert, Tobias$$b0
000308544 245__ $$aComparative validation of surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation in endoscopy: Results of the PhaKIR 2024 challenge.
000308544 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2026
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000308544 520__ $$aReliable recognition and localization of surgical instruments in endoscopic video recordings are foundational for a wide range of applications in computer- and robot-assisted minimally invasive surgery (RAMIS), including surgical training, skill assessment, and autonomous assistance. However, robust performance under real-world conditions remains a significant challenge. Incorporating surgical context - such as the current procedural phase - has emerged as a promising strategy to improve robustness and interpretability. To address these challenges, we organized the Surgical Procedure Phase, Keypoint, and Instrument Recognition (PhaKIR) sub-challenge as part of the Endoscopic Vision (EndoVis) challenge at MICCAI 2024. We introduced a novel, multi-center dataset comprising thirteen full-length laparoscopic cholecystectomy videos collected from three distinct medical institutions, with unified annotations for three interrelated tasks: surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation. Unlike existing datasets, ours enables joint investigation of instrument localization and procedural context within the same data while supporting the integration of temporal information across entire procedures. We report results and findings in accordance with the BIAS guidelines for biomedical image analysis challenges. The PhaKIR sub-challenge advances the field by providing a unique benchmark for developing temporally aware, context-driven methods in RAMIS and offers a high-quality resource to support future research in surgical scene understanding.
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000308544 650_7 $$2Other$$aInstrument instance segmentation
000308544 650_7 $$2Other$$aInstrument keypoint estimation
000308544 650_7 $$2Other$$aRobot-assisted surgery
000308544 650_7 $$2Other$$aSurgical phase recognition
000308544 7001_ $$aRauber, David$$b1
000308544 7001_ $$aMaerkl, Raphaela$$b2
000308544 7001_ $$aKlausmann, Leonard$$b3
000308544 7001_ $$aYildiran, Suemeyye R$$b4
000308544 7001_ $$aGutbrod, Max$$b5
000308544 7001_ $$aNunes, Danilo Weber$$b6
000308544 7001_ $$aMoreno, Alvaro Fernandez$$b7
000308544 7001_ $$aLuengo, Imanol$$b8
000308544 7001_ $$aStoyanov, Danail$$b9
000308544 7001_ $$aToussaint, Nicolas$$b10
000308544 7001_ $$aCho, Enki$$b11
000308544 7001_ $$aKim, Hyeon Bae$$b12
000308544 7001_ $$aChoo, Oh Sung$$b13
000308544 7001_ $$aKim, Ka Young$$b14
000308544 7001_ $$aKim, Seong Tae$$b15
000308544 7001_ $$aArantes, Gonçalo$$b16
000308544 7001_ $$aSong, Kehan$$b17
000308544 7001_ $$aZhu, Jianjun$$b18
000308544 7001_ $$aXiong, Junchen$$b19
000308544 7001_ $$aLin, Tingyi$$b20
000308544 7001_ $$aKikuchi, Shunsuke$$b21
000308544 7001_ $$aMatsuzaki, Hiroki$$b22
000308544 7001_ $$aKouno, Atsushi$$b23
000308544 7001_ $$aManesco, João Renato Ribeiro$$b24
000308544 7001_ $$aPapa, João Paulo$$b25
000308544 7001_ $$aChoi, Tae-Min$$b26
000308544 7001_ $$aJeong, Tae Kyeong$$b27
000308544 7001_ $$aPark, Juyoun$$b28
000308544 7001_ $$aAlabi, Oluwatosin$$b29
000308544 7001_ $$aWei, Meng$$b30
000308544 7001_ $$aVercauteren, Tom$$b31
000308544 7001_ $$aWu, Runzhi$$b32
000308544 7001_ $$aXu, Mengya$$b33
000308544 7001_ $$aWang, An$$b34
000308544 7001_ $$aBai, Long$$b35
000308544 7001_ $$aRen, Hongliang$$b36
000308544 7001_ $$0P:(DE-HGF)0$$aYamlahi, Amine$$b37
000308544 7001_ $$0P:(DE-He78)19525b4b76d116daa9394a3e4f6b7233$$aHennighausen, Jakob$$b38
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000308544 7001_ $$aKondo, Satoshi$$b40
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000308544 7001_ $$aHirasawa, Kousuke$$b42
000308544 7001_ $$aYang, Shu$$b43
000308544 7001_ $$aWang, Yihui$$b44
000308544 7001_ $$aChen, Hao$$b45
000308544 7001_ $$aRodríguez, Santiago$$b46
000308544 7001_ $$aAparicio, Nicolás$$b47
000308544 7001_ $$aManrique, Leonardo$$b48
000308544 7001_ $$aLyons, Juan Camilo$$b49
000308544 7001_ $$aHosie, Olivia$$b50
000308544 7001_ $$aAyobi, Nicolás$$b51
000308544 7001_ $$aArbeláez, Pablo$$b52
000308544 7001_ $$aLi, Yiping$$b53
000308544 7001_ $$aAl Khalil, Yasmina$$b54
000308544 7001_ $$aNasirihaghighi, Sahar$$b55
000308544 7001_ $$0P:(DE-He78)191434cf815e27a18a86287bacc2d496$$aSpeidel, Stefanie$$b56
000308544 7001_ $$aRueckert, Daniel$$b57
000308544 7001_ $$aFeussner, Hubertus$$b58
000308544 7001_ $$aWilhelm, Dirk$$b59
000308544 7001_ $$aPalm, Christoph$$b60
000308544 773__ $$0PERI:(DE-600)1497450-2$$a10.1016/j.media.2026.103945$$gVol. 109, p. 103945 -$$p103945$$tMedical image analysis$$v109$$x1361-8415$$y2026
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