National Lung Screening Trial
This collection contains subjects from a randomized controlled clinial trial of screening tests for lung cancer conducted by the National Lung Screening Trial (NLST), between August 2002 and April 2004.
The osteosarcoma dataset is composed of digitized Hematoxylin and eosin (H&E) stained osteosarcoma histology images from adolescents. The data was collected by a team of clinical scientists at University of Texas Southwestern Medical Center, Dallas.
This collection comprises a total of 28 3 Tesla T1-weighted, T2-weighted, Diffusion weighted and Dynamic Contrast Enhanced prostate MRI along with accompanying digitized histopathology (H&Estained) images of corresponding radical prostatectomy specimens.
This is the first attempt of mapping the extent of Invasive Adenocarcinoma onto in vivo lung CT. The mappings constitute ground truth of disease and may be used to further investigate the imaging signatures of Invasive Adenocarcinoma in ground glass pulmonary nodules. Data collection and analysis was provided by Case Western Reserve University.
The Munich AML Morphology Dataset contains 18,365 expert-labeled single-cell images taken from patients diagnosed with Acute Myeloid Leukemia at Munich University Hospital. The dataset has been used by the authors to train a convolutional neural network for single-cell morphology classification.
The Post-NAT-BRCA dataset is a collection of representative sections from breast resections in patients with residual invasive breast cancer following neoadjuvant therapy. Histologic sections were prepared and digitized to produce high resolution, microscopic images of treated breast cancer tumors.
The dataset consists of 130 de-identified whole slide images (WSI) of H&E stained axillary lymph node specimens from 78 patients. Metastatic breast carcinoma is present in 36 of the WSI from 27 patients.
This data collection consists of 15,135 acute lymphoblastic leukemia (ALL) images which were split into 3 separate testing phases for the purpose of training a machine learning-based algorithm. The dataset was used for the IEEE ISBI 2019 conference challenge.
This data collection consists of 85 Jenner-Giemsa stained bone marrow aspirate slides of patients diagnosed with multiple myeloma. Images were captured in raw BMP formate with a size of 2560×1920 pixels.
Microscopic images were captured from bone marrow aspirate slides of patients diagnosed with B-lineage Acute Lymphoid Leukemia (B-ALL) and Multiple Myeloma (MM) as per the standard guidelines. This dataset consists of 90 images of B-ALL and 100 images of MM.
This data collection consists of MRI/CT scan data as well as clinical and genomic pathology data for brain tumor patients that form the cohort for the resource Ivy Glioblastoma Atlast Project (Ivy GAP). There are 390 studies for 39 patients that include pre-surgery, post-surgery and follow up scans.