MuCeD, a dataset that is carefully curated and validated by expert pathologists from the All India Institute of Medical Science (AIIMS), Delhi, India. The H&E-stained histopathology images of the human duodenum in MuCeD are captured through an Olympus BX50 microscope at 20x zoom using a DP26 camera with each image being 1920x2148 in dimension. The dataset has 55 images, with bounding boxes for 2,090 IELs and 6,518 ENs annotated using the LabelMe software and are further validated by multiple pathologists. These cells are selected from the epithelial area -- a region of interest that has been explicitly segmented by experts. The epithelial area denotes the area of continuous villi and is used for cell detection, whereas rest of the area is masked out. Further, each image is sliced into 9 subimages and each subimage is re-scaled to 640x640, before it is given as input to object detection models. We divide 55 images into five folds of 11 images each and report 5-fold crossvalidation numbers. Within 44 training images in a given fold, 8 are used for validation and 36 for training.
Data is annotated in yolo format with labels are present in .txt files with class x, y, width, heigh format.