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Kaggle Glaucoma Detection
The dataset used in the paper to evaluate the proposed two-stage approximately orthogonal training framework (TAOTF) for Deep Neural Networks (DNNs). -
Kaggle APTOS 2019
The dataset used in the paper to evaluate the proposed two-stage approximately orthogonal training framework (TAOTF) for Deep Neural Networks (DNNs). -
Colorectal Liver Metastases Survival Prediction Dataset
The dataset used in this paper is a collection of histological slides stained with Hematoxylin and Eosin (H&E) and Hematoxylin Phloxine Saffron (HPS) for colorectal liver... -
The Cancer Imaging Archive (TCIA)
The dataset used in this study is from the Brain Tumor Radiogenomic Classification challenge (Baid et al., 2021) that includes multi-parametric MRI (mpMRI) scans for 585... -
FastMRI knee raw data 1
The FastMRI knee raw data 1 was acquired from a 3T Siemens scanner (Siemens Magnetom Skyra, Prisma and Biograph mMR). Data acquisition used a 15 channel knee coil array and... -
NIH pancreas segmentation dataset
The NIH pancreas segmentation dataset contains 82 abdominal CT volumes. The width and height of each volume are 512, while the axial view slice number can vary from 181 to 466.... -
Chest X-ray Images (Pneumonia) dataset
The dataset used in this paper for pneumonia detection on chest X-ray images. -
COVID-19 pneumonia dataset
The proposed model uses integrative CT images for the COVID-19 dataset, including 1521 patients with or without COVID-19 pneumonia and their recorded clinical features epidemic. -
Routine Colon Cancer (RCC) detection dataset
The dataset for nuclei detection task. -
Nuclei Segmentation Challenge 2018 dataset
The dataset for nuclei segmentation task. -
Routine Colon Cancer (RCC) classification and detection dataset
The dataset for nuclei classification, segmentation, and detection tasks. -
GenerateCT: Text-Conditional Generation of 3D Chest CT Volumes
The dataset comprises 25,701 non-contrast 3D chest CT volumes with a 512×512 resolution and varying axial slice counts ranging from 100 to 600. These volumes originate from... -
HNSCC-3DCT-RT Dataset
The HNSCC-3DCT-RT dataset is a real CT image of the human brain used for testing the proposed method. -
Shepp-Logan Phantom
The dataset used in the paper is a Shepp-Logan phantom, a high-resolution image of size 2563 and a low-resolution image of 1283 voxels. -
Fluorescein Angiography dataset
The dataset is used for training and testing the proposed VTGAN model for fundus-to-angiogram synthesis and disease prediction. -
MRBrainS18 dataset
The dataset used for self-supervised learning of 3D medical images. -
Low-dose CT dataset
The dataset for low-dose CT image enhancement and segmentation. -
Alphabet SCM, Voronoi SCM, Flag SCM, VT-SOM
The dataset used to evaluate the capacity of a denoising diffusion probabilistic model to reproduce spatial context in medical imaging. -
Deep ensemble learning for segmenting tuberculosis-consistent manifestations ...
Automated segmentation of tuberculosis (TB)-consistent lesions in chest X-rays (CXRs) using deep learning (DL) methods can help reduce radiologist effort, supplement clinical...
