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 smart phones 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 smart phone.
The wound image is captured by
the camera on the smart phone
with the assistance of an image capture box. After that, the smart phone
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.
AIM
The
aim of this paper is propose a novel wound
image analysis system
implemented solely on the Android smart
phone.
SCOPE
The
scope of this paper is tends to show that our system
can be efficiently used to analyze the wound
healing status with promising accuracy
EXISTING SYSTEM:
There
are several problems with current practices for treating diabetic foot ulcers. First,
patients must go to their wound clinic on a regular basis to have their wounds
checked by their clinicians. This need for frequent clinical evaluation is not
only inconvenient and time consuming for patients and clinicians, but also
represents a significant health care cost because patients may require special
transportation, e.g., ambulances. Second, a clinician’s wound assessment
process is based on visual examination. He/she describes the wound by its
physical dimensions and the color of its tissues, providing important
indications of the wound type and the stage of healing. Because the visual
assessment does not produce objective measurements and quantifiable parameters
of the healing status, tracking a wound’s healing process across consecutive
visits is a difficult task for both clinicians and patients. The wound boundary
determination was done with a particular implementation of the level set
algorithm; specifically the distance regularized level set evolution The
principal disadvantage of the level set algorithm is that the iteration of
global level set function is too computationally intensive to be implemented on
smart phones, even with the narrow band confined implementation based on GPUs. In
addition, the level set evolution completely depends on the initial curve which
has to be pre-delineated either manually or by a well-designed algorithm.
Finally, false edges may interfere with the evolution when the skin color is
not uniform enough and when missing boundaries, as frequently occurring in
medical images, results in evolution leakage (the level set evolution does not
stop properly on the actual wound boundary). Hence, a better method was
required to solve these problems.
DISADVANTAGES:
- Patient has to travel with foot ulcers to their clinics to report about the ulcers. This may increase the seriousness of the ulcers instead of curing it.
- Patient travel exposure may cause a serious problem for them.
PROPOSED SYSTEM:
In this paper, replaced the level set algorithms with the
efficient mean-shift segmentation algorithm. While it addresses the previous problems,
it also creates additional challenges, such as over-segmentation, which we
solved using the region adjacency graph (RAG)-based region merge
algorithm. Present the entire process of recording and analyzing a wound image,
using algorithms that are executable on a smart phone, and provide evidence of
the efficiency and accuracy of these algorithms for analyzing diabetic foot
ulcers.
ADVANTAGES
- Patient’s travel exposure is considerably reduced. Also it will reduce the patients stress.
- Doctor can easily analyze the problem through images and its segmentation. So the proper report can be given to the patient on time
SYSTEM CONFIGURATION
HARDWARE REQUIREMENTS:-
· Processor - Pentium –III
·
Speed - 1.1 Ghz
·
RAM - 256 MB(min)
·
Hard
Disk - 20 GB
·
Floppy
Drive - 1.44 MB
·
Key
Board - Standard Windows Keyboard
·
Mouse - Two or Three Button Mouse
·
Monitor -
SVGA
SOFTWARE REQUIREMENTS:-
·
Operating
System :Android OS
·
Front
End : JAVA
·
Database
: SqLite
·
Tool :Eclipse
REFERENCES
Pedersen,
P.C. Strong, D.M. Tulu, B.,Lei Wang
,"SMARTPHONE-BASED WOUND ASSESSMENT SYSTEM FOR PATIENTS WITH
DIABETES" , IEEE Transactions on
Biomedical Engineering Volume 62 ,
Issue 2 Feb. 2015
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