Resources

31 results for "segmentation"

Database Credentialed Access

Chest X-ray Dataset with Lung Segmentation

Wimukthi Indeewara, Mahela Hennayake, Kasun Rathnayake, et al.

Chest X-ray(CXR) images are prominent among medical images and are commonly administered in emergency diagnosis and treatment corresponding to cardiac and respiratory diseases. Though there are robust solutions available for medical diagnosis, valid…
Published: Feb. 8, 2023. Version: 1.0.0
Database Credentialed Access

MIMIC-CXR-Ext-ILS: Lesion Segmentation Masks and Instruction-Answer Pairs for Chest X-rays

Geon Choi, Hangyul Yoon, Hyunju Shin, et al.

The applicability of current lesion segmentation models for chest X-rays (CXRs) has been limited both by a small number of target labels and the reliance on complex, expert-level text inputs, creating a barrier to practical use. To address these lim…
Published: March 25, 2026. Version: 1.0.0
Database Open Access

Heart and lung segmentations for MIMIC-CXR/MIMIC-CXR-JPG and Montgomery County TB databases

Benjamin Duvieusart, Felix Krones, Guy Parsons, et al.

Segmenting the heart and lungs from chest X-ray images is essential for accurate disease diagnosis, enabling the calculation of image-derived digital biomarkers for cardiopulmonary health assessment. Furthermore, creation of annotated data sets can …
Published: Aug. 14, 2023. Version: 1.0.0
Database Credentialed Access

Chest X-ray segmentation images based on MIMIC-CXR

Li-Ching Chen, Po-Chih Kuo, Ryan Wang, et al.

As more and more artificial intelligence (AI) or deep learning technologies have been applied to medical image applications such as radiological finding identification in chest X-rays (CXRs), the interpretability of the prediction model is crucial f…
Published: Aug. 18, 2022. Version: 1.0.0
Database Open Access

CheXmask Database: a large-scale dataset of anatomical segmentation masks for chest x-ray images

Nicolas Gaggion, Candelaria Mosquera, Martina Aineseder, et al.

The CheXmask Database presents a comprehensive, uniformly annotated collection of chest radiographs, constructed from five public databases: ChestX-ray8, Chexpert, MIMIC-CXR-JPG, Padchest and VinDr-CXR. The database aggregates 657,566 anatomical seg…
Published: Jan. 22, 2025. Version: 1.0.0
Software Open Access

Logistic Regression-HSMM-based Heart Sound Segmentation

David Springer

The identification of the exact positions of the first and second heart sounds within a phonocardiogram (PCG), or heart sound segmentation, is an essential step in the automatic analysis of heart sound recordings, allowing for the classification of …
Published: July 29, 2019. Version: 1.0
Database Open Access

CheXmask-U: Uncertainty Estimation for Landmark-Based Anatomical Segmentation Masks in Chest X-ray Images

Matias Cosarinsky, Nicolas Gaggion, Enzo Ferrante

We present an extended version of the CheXmask dataset, augmenting the original anatomical segmentation masks of chest X-rays with node-wise uncertainty estimates. The dataset retains the comprehensive coverage of five public sources—ChestX-ray8, Ch…
Published: Sept. 2, 2026. Version: 1.0.0
Database Restricted Access

Endoscapes2023, A Critical View of Safety and Surgical Scene Segmentation Dataset for Laparoscopic Cholecystectomy

Pietro Mascagni, Deepak Alapatt, Aditya Murali, et al.

Minimally invasive image-guided surgery heavily relies on vision. Deep learning models for surgical video analysis can support surgeons in visual tasks such as assessing the critical view of safety (CVS) in laparoscopic cholecystectomy, potentially …
Published: Dec. 11, 2024. Version: 1.0.0
Database Restricted Access

Dataset for Segmentation and Classification of Cardiac Implantable Electronic Devices in Chest X-Rays

Keno Bressem, Felix Busch, Andrei Zhukov, et al.

This dataset encompasses a comprehensive collection of 2,321 chest radiographs (originally DICOM, converted to PNG) and 11,072 smartphone images documenting various cardiac implantable electronic devices (CIEDs) such as implantable pacemakers, cardi…
Published: March 4, 2025. Version: 1.0.0
Database Open Access

MAMA-MIAAI - Here We Go Again: An Extended Breast MRI Dataset with Bias Field Correction and Automated Breast Tissue Segmentation for Radiomics and AI Research

Florian Schwarzhans, Palak Handa, Laura Atenea Villazan Garcia, et al.

The publicly available MAMA-MIA breast dynamic contrast-enhanced magnetic resonance imaging (MRI) dataset has become an important resource for artificial intelligence (AI) research on breast cancer, particularly for tumor detection and predicting pa…
Published: Oct. 13, 2026. Version: 1.0.0