4 papers · 1 filter
Temporally Consistent Label Interpolation for Robust Surgical Multi-Task Learning under Challenging Conditions
Garam Kim, Juyoun Park
Effective multi-task learning for surgical scene understanding is fundamentally hindered by annotation granularity mismatch; temporal workflow tasks such as phase recognition, step…
SurgMLLMBench: A Multimodal Large Language Model Benchmark Dataset for Surgical Scene Understanding
Tae-Min Choi, Tae Kyeong Jeong, Garam Kim +6
Recent advances in multimodal large language models (LLMs) have highlighted their potential for medical and surgical applications. However, existing surgical datasets predominantly…
Microsurgical Instrument Segmentation for Robot-Assisted Surgery
Tae Kyeong Jeong, Garam Kim, Juyoun Park
Accurate segmentation of thin structures is critical for microsurgical scene understanding but remains challenging due to resolution loss, low contrast, and class imbalance. We pro…
Surgical Video Understanding with Label Interpolation
Garam Kim, Tae Kyeong Jeong, Juyoun Park
Robot-assisted surgery (RAS) has become a critical paradigm in modern surgery, promoting patient recovery and reducing the burden on surgeons through minimally invasive approaches.…