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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... -
Enhanced generative adversarial network for 3D brain MRI super-resolution
Single image super-resolution (SISR) reconstruction for magnetic resonance imaging (MRI) has generated significant interest because of its potential to not only speed up imaging... -
Fine-tuning of WMn network for CSFn-MPRAGE images
A fine-tuning approach was employed to incorporate information learned from the WMn network to segment thalamic nuclei from CSFn-MPRAGE images, which have poor intra-thalamic... -
Automated Thalamic Nuclei Segmentation Using Multi-Planar Cascaded Convolutio...
A cascaded multi-planar scheme with a modified residual U-Net architecture was used to segment thalamic nuclei on conventional and white-matter-nulled (WMn) magnetization... -
MRSpineSeg Challenge
The MRSSegClg dataset is used for external testing of the proposed method. -
Denoising diffusion-based MRI to CT translation enables automated spinal segm...
This study successfully demonstrated the feasibility of translating standard sagittal spine MRI into the CT domain, enabling subsequent CT-based image processing.
