766 datasets found

Anomaly detection is the process of identifying atypical data samples that significantly deviate from the majority of the dataset. In the realm of clinical screening and...

Glioblastoma brain tumor detection and segmentation using preprocessed brain MRI images

Progressive growing of GANs for improved quality, stability, and variation.

Stain-transforming cycle-consistent generative adversarial networks for improved segmentation of renal histopathology.

A custom pipeline (histo-fetch) to efficiently extract random patches and labels from pathology whole slide images (WSIs) for input to a neural network on-the-fly.

The dataset used for testing and validation of the proposed Monte Carlo Transformer-based U-Net (MC-Swin-U) architecture for tumor and OAR segmentation in radiation oncology...

The dataset used in the paper is a collection of medical images of patients diagnosed with glioblastoma multiforme, which is a type of brain cancer.

Organ at risk (OAR) segmentation is a crucial step for treatment planning and outcome determination in radiotherapy treatments of cancer patients.

A dataset of non-contrast CT images and their corresponding contrast-enhanced CT angiograms for abdominal aortic aneurysms

A text-image embedding network for common thorax disease classification and reporting in chest x-rays.

A hospital-scale chest x-ray database and benchmarks for weakly-supervised classification and localization of common thorax diseases.

The MIMIC-CXR dataset is currently the largest radiology imaging dataset available. It comprises a total of 473,057 chest X-ray images and 206,563 associated radiology...

Chest radiography is a relatively cheap, widely available medical procedure that conveys key information for making diagnostic decisions. Chest X-rays are frequently used in the...

Replicated the model described in Rajpurkar et al. with fixed hyperparameters and 50 different random seeds to identify 14 findings in chest radiographs.

The LoDoPaB-CT dataset is used to test the reconstruction methods. The dataset consists of 284,672 training samples and 10,000 test samples.

The dataset is used for automatic method for detecting Age-related Macular Degeneration (AMD) lesions in RGB eye fundus images.

The LPBA40 dataset contains 3D brain MRI scans of 40 healthy adults, with image dimensions of 256×124×256 and a voxel size of 0.8938×1.500×0.8594 mm³. Each scan is precisely...

The dataset used in this paper for dynamic multi-coil MR image reconstruction using non-uniformly sampled data.

The dataset used in the paper is a collection of medical images of patients diagnosed with glioblastoma multiforme, which is a type of brain cancer.

The Curated Breast Imaging Subset of Digital Database of Screening Mammography (CBIS-DDSM) dataset is used for both training and testing of the developed deep learning approach.