Statistical modeling and recognition of surgical workflow

By Nicolas Padoy, Tobias Blum, Seyed-Ahmad Ahmadi, Hubertus Feußner, Marie-Odile Berger, Nassir Navab. Medical Image Anal., 2012

303 citations recorded by the source corpus.

Subfields: Surgery, Signal Processing

View Paper: https://www.semanticscholar.org/paper/04b0108f3a385f3ef7905d4399cad13a8c44d31a

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In Signal Processing

1. P. Heng
2. Qi-Yan Dou
3. Hao Chen

Citations in the corpus

• EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos (2016, methodology): “, if the network is optimized to carry out not only phase recognition, but also tool presence detection; • since the tool signals have been successfully used to carry out phase recognition in previous work [3], [5], [9], the inclusion of automatically generated tool detection signals”
• SV-RCNet: Workflow Recognition From Surgical Videos Using Recurrent Convolutional Network (2018, methodology): “Diverse attempts have been made to recognize the surgical workflow or phase, by using various information, including binary instrument usage signals [7], RFID tags [8], data acquired via sensors on tool tracking devices [9], and surgical robots [10].”