Visual Grounding - Endoscopic Third Ventriculostomy (VG-ETV) dataset

This dataset comprises 1718 annotated images extracted from 29 video clips recorded during Endoscopic Third Ventriculostomy (ETV) procedures, each captured at a frame rate of 25 FPS. Out of these images, 1645 are allocated for the training set, while the remainder is designated for the testing set. The images contain a total of 4013 anatomical or intracranial structures, annotated with bounding boxes and class names for each structure. Additionally, there are at least three language descriptions of varying technicality levels provided for each structure. This dataset offers a rich resource for tasks such as visual grounding (VG) or referring expressions comprehension (REC) and classification. Importantly, it addresses a critical gap in the availability of specialized surgical datasets, providing researchers with invaluable data to advance research in the surgical domain.