5 bone segmentation masks and 15 annotations of anatomical landmarks for pelvis bones in each of 90 Computed Tomography (CT) cases extracted from the CT Lymph nodes and CT Colonography collections from the The Cancer Imaging Archive (TCIA).
Keywords: Radiology, Annotated, Pelvis, CT, Computed tomography, Anatomical landmarks, Bone segmentation.
Sample images
Sample images with reduced image quality. Please click to preview.
Dataset information
| Short name | CTPEL |
|---|---|
| Cite as | Bryan Connolly and Chunliang Wang (2019) Segmented CT pelvis scans with annotated anatomical landmarks doi:10.23698/aida/ctpel |
| Field | Radiology |
| Organ |
Pelvis |
| Age span | |
| Title | Segmented CT pelvis scans with annotated anatomical landmarks |
| Author |
Bryan Connolly
Chunliang Wang |
| Year | 2019 |
| DOI | doi:10.23698/aida/ctpel |
| Status | Ongoing |
| Version | 1.0 |
| Scans | 90 |
| Annotations | 1800 |
| Size | 28.0GB |
| Resolution | |
| Modality |
CT
|
| Scanner |
|
| Stain | |
| Phase | |
| References | |
| Access constraints |
Controlled access
AIDA license
|
| Copyright | Copyright 2019 KTH, Chunliang Wang |
| Download | Please contact Chunliang Wang, Joel Hedlund, or Claes Lundstrom to request access. |
Annotation
Segmentation was done first with an interactive software (Mialab), followed by manual inspection and correction using ITKSNAP. The interactive method is based on fuzzy connectedness followed by level set method. Both the segmentation mask and annotated anatomical landmarks were created by a trained radiologist.
File formats
Importing binary masks to numpy
The dataset contains a DICOM SEG file, which can be converted to an ITK image file (mha, nifti, etc) by using dcmqi and the command line tool segimage2itkimage, which is straightforward to read into a numpy array.
License
Controlled access
Free for use in legal and ethical medical diagnostics research. Please contact the copyright holder for terms of access.
AIDA BY license
Segmentation masks and anatomical landmark annotations
License v1.2.1
Copyright 2019 KTH, Chunliang Wang
Permission to use, copy, modify, and/or distribute the data within AIDA (Analytic Imaging Diagnostics Arena https://medtech4health.se/aida) for the purpose of medical imaging research with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies.
THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS DATA.
Attribution
In addition to the TCIA rules about using the image data, we would really appreciate if you include the following references in publications that make use of the provided segmentation masks or anatomical landmarks:
[1] Bryan Connolly and Chunliang Wang (2019) Segmented CT pelvis scans with annotated anatomical landmarks doi:10.23698/aida/ctpel.