GBCU is the first public dataset for Gallbladder Cancer identification from Ultrasound images. GBCU contains a total of 1255 (432 normal, 558 benign, and 265 malignant) annotated abdominal Ultrasound images collected from 218 patients. Of the 218 patients, 71, 100, and 47 were from the normal, benign, and malignant classes, respectively. The sizes of the training and testing sets are 1133 and 122, respectively. To ensure generalization to unseen patients, all images of any particular patient were either in the train or the test split. We acquired data samples from patients referred to PGIMER, Chandigarh (a referral hospital in Northern India) for abdominal ultrasound examinations of suspected Gallbladder pathologies. The study was approved by the Ethics Committee of PGIMER, Chandigarh. We obtained informed written consent from the patients at the time of recruitment, and protect their privacy by fully anonymizing the data. Grayscale B-mode static images, including both sagittal and axial sections, were recorded by radiologists for each patient using a Logiq S8 machine.

Each image is labeled as one of the three classes - normal, benign, or malignant. The ground-truth labels were biopsy-proven to assert the correctness. Additionally, bounding-box annotations for abnormal pathologies (e.g. stone, benign mural thickening, or malignancy), and the GB are provided.

The GBCU dataset is suitable for both image classification and object detection tasks. Apart from the Gallbladder Cancer, the dataset can also be used for detection of several other pathologies.