Literature DB >> 25248175

Smartphone-based wound assessment system for patients with diabetes.

Lei Wang, Peder C Pedersen, Diane M Strong, Bengisu Tulu, Emmanuel Agu, Ronald Ignotz.   

Abstract

Diabetic foot ulcers represent a significant health issue. Currently, clinicians and nurses mainly base their wound assessment on visual examination of wound size and healing status, while the patients themselves seldom have an opportunity to play an active role. Hence, a more quantitative and cost-effective examination method that enables the patients and their caregivers to take a more active role in daily wound care potentially can accelerate wound healing, save travel cost and reduce healthcare expenses. Considering the prevalence of smartphones with a high-resolution digital camera, assessing wounds by analyzing images of chronic foot ulcers is an attractive option. In this paper, we propose a novel wound image analysis system implemented solely on the Android smartphone. The wound image is captured by the camera on the smartphone with the assistance of an image capture box. After that, the smartphone performs wound segmentation by applying the accelerated mean-shift algorithm. Specifically, the outline of the foot is determined based on skin color, and the wound boundary is found using a simple connected region detection method. Within the wound boundary, the healing status is next assessed based on red-yellow-black color evaluation model. Moreover, the healing status is quantitatively assessed, based on trend analysis of time records for a given patient. Experimental results on wound images collected in UMASS-Memorial Health Center Wound Clinic (Worcester, MA) following an Institutional Review Board approved protocol show that our system can be efficiently used to analyze the wound healing status with promising accuracy.

Entities:  

Mesh:

Year:  2014        PMID: 25248175     DOI: 10.1109/TBME.2014.2358632

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  18 in total

Review 1.  High Efficiency Video Coding (HEVC)-Based Surgical Telementoring System Using Shallow Convolutional Neural Network.

Authors:  Ali Hassan; Mubeen Ghafoor; Syed Ali Tariq; Tehseen Zia; Waqas Ahmad
Journal:  J Digit Imaging       Date:  2019-12       Impact factor: 4.056

Review 2.  Diagnostic and Prognostic Utility of Non-Invasive Multimodal Imaging in Chronic Wound Monitoring: a Systematic Review.

Authors:  Rashmi Mukherjee; Suman Tewary; Aurobinda Routray
Journal:  J Med Syst       Date:  2017-02-13       Impact factor: 4.460

3.  Data protection: in our patients' hands.

Authors:  L E Thomson; Hlp Bates
Journal:  Ann R Coll Surg Engl       Date:  2016-09-23       Impact factor: 1.891

4.  Boundary determination of foot ulcer images by applying the associative hierarchical random field framework.

Authors:  Lei Wang; Peder C Pedersen; Emmanuel Agu; Diane Strong; Bengisu Tulu
Journal:  J Med Imaging (Bellingham)       Date:  2019-04-21

5.  Fine-grained diabetic wound depth and granulation tissue amount assessment using bilinear convolutional neural network.

Authors:  Xixuan Zhao; Ziyang Liu; Emmanuel Agu; Ameya Wagh; Shubham Jain; Clifford Lindsay; Bengisu Tulu; Diane Strong; Jiangming Kan
Journal:  IEEE Access       Date:  2019-12-12       Impact factor: 3.367

6.  An Automatic Assessment System of Diabetic Foot Ulcers Based on Wound Area Determination, Color Segmentation, and Healing Score Evaluation.

Authors:  Lei Wang; Peder C Pedersen; Diane M Strong; Bengisu Tulu; Emmanuel Agu; Ron Ignotz; Qian He
Journal:  J Diabetes Sci Technol       Date:  2015-08-07

7.  Processing Diabetes Mellitus Composite Events in MAGPIE.

Authors:  Albert Brugués; Stefano Bromuri; Michael Barry; Óscar Jiménez Del Toro; Maciej R Mazurkiewicz; Przemyslaw Kardas; Josep Pegueroles; Michael Schumacher
Journal:  J Med Syst       Date:  2015-11-21       Impact factor: 4.460

Review 8.  Health Sensors, Smart Home Devices, and the Internet of Medical Things: An Opportunity for Dramatic Improvement in Care for the Lower Extremity Complications of Diabetes.

Authors:  Rami Basatneh; Bijan Najafi; David G Armstrong
Journal:  J Diabetes Sci Technol       Date:  2018-04-11

9.  Wound Size Imaging: Ready for Smart Assessment and Monitoring.

Authors:  Yves Lucas; Rania Niri; Sylvie Treuillet; Hassan Douzi; Benjamin Castaneda
Journal:  Adv Wound Care (New Rochelle)       Date:  2020-09-25       Impact factor: 4.730

Review 10.  The DFUC 2020 Dataset: Analysis Towards Diabetic Foot Ulcer Detection.

Authors:  Bill Cassidy; Neil D Reeves; Joseph M Pappachan; David Gillespie; Claire O'Shea; Satyan Rajbhandari; Arun G Maiya; Eibe Frank; Andrew Jm Boulton; David G Armstrong; Bijan Najafi; Justina Wu; Rupinder Singh Kochhar; Moi Hoon Yap
Journal:  touchREV Endocrinol       Date:  2021-04-28
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