Head-CT 2D/3D images with and without ICH prepared for Deep Learning

Abstract

For the "ICH detection" part, radiologists selected parients according to inclusion and exclusion criteria. - Images with HIC: - Inclusion criteria: Diagnosis of an ICH between 2010 and 2015. - Exclusion criteria: Significant motion artifact Significant postsurgical changes. - Images without ICH (healthy): - Inclusion criteria: Having done a head-CT between 2010 and 2015 reported as “normal” or “ICH is ruled out”. - Exclusion criteria: Significant motion artifact. Other major diagnoses (such as tumors). For the "prognosis" part, only the pathological head-CTs were used. All images are de-identified.In order to access this dataset, it is necessary to send an email to [email protected] specifying the intended use. Commercial use is prohibited under license: Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA).Para poder acceder a este dataset es necesario enviar un email a [email protected] especificando el uso que se le va a dar. Se prohíbe su uso comercial bajo la licencia Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA).[EN] This dataset contains two sets of images and tabular data anonymised and prepared for its use in the training and/or validation of artificial neural networks. The first set of images includes 3322 JPG files with 2D images of head computed tomography (CT) scans with and without intracranial hemorrhage (ICH), as well as a CSV with demographic data (age and gender) associated to each file. The second set of images consists of 262 NPY files with 3D images of head-CT scans with ICH, together with a CSV that includes clinical data related to each image.[ES] Este dataset contiene dos conjuntos de imágenes y datos tabulares anonimizados y preparados para su uso en el entrenamiento o validación de redes neuronales artificiales. El primer conjunto de imágenes incluye 3322 archivos JPG con imágenes 2D de tomografías computarizadas (TCs) craneales sin y con hemorragia intracranial (HIC), así como un CSV con datos demográficos (edad y sexo) asociados a cada archivo. El segundo conjunto de imágenes consiste en 262 archivos NPY con imágenes 3D de TCs con HIC junto con un CSV que incluye varios datos clínicos asociados a las imágenes.Peer reviewe