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abd-skin-segmentation · MRE-Lab-UMD

Deep learning techniques for skin segmentation on novel abdominal dataset. Work conducted as part of the development process of an autonomous robotic ultrasound system.

robot demonstrations
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Resource screenshot · captured 2026-10-10 · visually reviewed

Overview

Deep learning techniques for skin segmentation on novel abdominal dataset. Work conducted as part of the development process of an autonomous robotic ultrasound system.

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Project information

Maintainer
MRE-Lab-UMD
Primary language
Jupyter Notebook
Repository code license
Apache-2.0
Model-weight license
Not recorded
Dataset license
Not recorded
Hardware design license
Not recorded
Maintenance
Not archived in the last recorded metadata
Last observed repository push
2021-04-05

Code licenses do not automatically cover model weights, datasets or hardware designs. Unrecorded license details require confirmation with the publisher.

Documentation sections

  • Deep Learning Techniques for Skin Segmentation on Novel Abdominal Dataset
  • Introduction
  • Robotic abdominal ultrasound system with the camera view of the abdominal region, and the corresponding segmented skin mask.
  • Information on Abdominal Skin Dataset
  • Sample pictures of the abdominal dataset depicting different skin color intensities and body complexions.
  • Improved segmentation results with the use of our proposed Abdominal dataset using U-Net. From left to right in columns: original image, ground truth, segmentation with the Abdominal dataset, and segmentation without the Abdominal dataset.

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