Nerve-UTP

This dataset was acquired by the Universidad Tecnológica de Pereira (https://www.utp.edu.co, accessed on 17 November 2021) and the Santa Mónica Hospital, Dosquebradas, Colombia. It contains 691 images of the following nerve structures: the sciatic nerve (287 instances), the ulnar nerve (221 instances), the median nerve (41 instances), and the femoral nerve (70 instances). A SONOSITE Nano-Maxx device was used, fixing a 640 × 480 pixel resolution. Each image was labeled by an anesthesiologist from the Santa Mónica Hospital. As prepossessing, morphological operations such as dilation and erosion were applied. Next, we defined a region of interest by computing the bounding box around each nerve structure. As a result, we obtained images holding a maximum resolution of 360 × 279 pixels. Lastly, we applied a data augmentation scheme to obtain the following samples: 861 sciatic nerve images, 663 ulnar nerve images, 123 median nerve images, and 210 femoral nerve images (1857 input samples)[1].

[1]

Random Fourier Features-Based Deep Learning Improvement with Class Activation Interpretability for Nerve Structure Segmentation

class image_segmentation.datasets.segmentation.nerve_utp.NerveUtp(split=[0.2, 0.2], seed: int = 42, id_: str = '1-GWZOz2WZBUiv3Ta5nQp0XNxbmU-1Uv7')

already_unzipped = False

static load_instance(root_name)

load_instance_by_id(id_img)