Razi Journal of Medical Sciences
مجله علوم پزشکی رازی
RJMS
Medical Sciences
http://rjms.iums.ac.ir
39
journal39
2228-7043
2228-7051
en
jalali
1392
10
1
gregorian
2014
1
1
20
115
online
1
fulltext
fa
ارتباط بیماری دیابت و اعتیاد با اثر انگشت
The relationship between addiction and diabetes with fingerprints
پوست
Dermatology
پژوهشي
Research
<font face="Times New Roman" size="3"> </font><p class="MsoNormal" style="margin: 0in 0in 0pt text-align: justify line-height: normal unicode-bidi: embed direction: rtl text-justify: kashida text-kashida: 0%" dir="rtl"><b><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">زمینه و هدف</span></b><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">:
پوست آدمی بیش از هر قسمتی از بدن در معرض خطرات، بیماریها و عوارض ناشی از کار
قرار دارد.</span><span dir="ltr"></span><span lang="AR-SA" style="font-family: "Times New Roman","serif" font-size: 9pt mso-bidi-font-family: "B Mitra" mso-bidi-font-size: 10.0pt" dir="ltr"><span dir="ltr"></span> </span><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">یکی
از کاربردهای مطالعه در زمینه ارتباط بیماریها با پوست، استفاده از اثر انگشت در
تشخیص بیماری و در نتیجه درمان به موقع آن است. در این پروژه تصاویر اثر انگشت
مربوط به چند بیماری سیستماتیک مانند دیابت و اعتیاد مورد بررسی قرار گرفت.<o:p /></span></p><font face="Times New Roman" size="3"> </font><p class="MsoNormal" style="margin: 0in 0in 0pt text-align: justify unicode-bidi: embed direction: rtl text-justify: kashida text-kashida: 0%" dir="rtl"><b><span lang="AR-SA" style="line-height: 115% font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">روش کار</span></b><span lang="AR-SA" style="line-height: 115% font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">:
اولین روشی که در تحلیل دادهها استفاده شده، روش </span><span style="line-height: 115% font-family: "Times New Roman","serif" font-size: 9pt mso-bidi-font-family: "B Mitra" mso-bidi-font-size: 10.0pt" dir="ltr">Power Spectrum</span><span dir="rtl"></span><span lang="AR-SA" style="line-height: 115% font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt"><span dir="rtl"></span> است. با توجه به
نتایج به دست آمده، روشهای دیگری برای استخراج ویژگی از تصاویر اثر انگشت بررسی
شد. ترکیب ویژگیهای بافتی که از ضرایب موجک استخراج میشوند، با ویژگیهای آماری
موجک، بردار ویژگی قویتری خواهد ساخت. در این تحقیق دو روش مبتنی بر ویژگیهای
آماری موجک و ویژگیهای بافت تصویر، برای تحلیل تصاویر اثر انگشت بیماران استفاده
شده است.</span><span lang="FA" style="font-family: "B Mitra" mso-bidi-language: FA mso-ascii-font-family: Calibri mso-hansi-font-family: Calibri"><o:p /></span></p><font face="Times New Roman" size="3"> </font><p class="MsoNormal" style="margin: 0in 0in 0pt text-align: justify line-height: normal unicode-bidi: embed direction: rtl text-justify: kashida text-kashida: 0%" dir="rtl"><b><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">یافتهها:</span></b><span lang="AR-SA" style="font-family: "B Mitra" font-size: 13pt mso-bidi-language: FA"> </span><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">تبدیل
موجک و ویژگیهای استخراجی از ضرایب موجک، در آنالیز تصاویر، قویتر از روشهای
مبتنی بر تبدیل فوریه مانند </span><span style="font-family: "Times New Roman","serif" font-size: 9pt mso-bidi-font-family: "B Mitra" mso-bidi-font-size: 10.0pt" dir="ltr">Power Spectrum</span><span dir="rtl"></span><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt"><span dir="rtl"></span> عمل میکنند.</span><span dir="ltr"></span><span lang="AR-SA" style="font-family: "Times New Roman","serif" font-size: 9pt mso-bidi-font-family: "B Mitra" mso-bidi-font-size: 10.0pt" dir="ltr"><span dir="ltr"></span> </span><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">روش
مبتنی بر ترکیب واریانس زیرباندهای موجک و ویژگیهای بافت بهترین نتایج را داشته
است، که در مورد اعتیاد 73 درصد و در مورد دیابت 67 درصد بوده است.</span><span lang="FA" style="font-family: "B Mitra" font-size: 12pt mso-bidi-language: FA mso-ascii-font-family: Calibri mso-hansi-font-family: Calibri"><o:p /></span></p><font face="Times New Roman" size="3"> </font><p class="MsoNormal" style="margin: 0in 0in 0pt text-align: justify line-height: normal unicode-bidi: embed direction: rtl text-justify: kashida text-kashida: 0%" dir="rtl"><b><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">نتیجه</span></b><b><span style="font-family: "Times New Roman","serif" font-size: 9pt mso-bidi-font-size: 10.0pt" dir="ltr"></span></b><b><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">گیری</span></b><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">:
نتایج این روشها</span><span dir="ltr"></span><span lang="AR-SA" style="font-family: "Times New Roman","serif" font-size: 9pt mso-bidi-font-family: "B Mitra" mso-bidi-font-size: 10.0pt" dir="ltr"><span dir="ltr"></span> </span><span lang="AR-SA" style="font-family: "B Mitra" font-size: 10pt mso-ascii-font-family: "Times New Roman" mso-hansi-font-family: "Times New Roman" mso-ansi-font-size: 9.0pt">در
تشخیص ارتباط بیماریها با اثر انگشت امیدوارکننده است. این موضوع نیازمند تحقیقات
بیشتر و عمیقتر است.<o:p /></span></p><font face="Times New Roman" size="3"> </font>
<font face="Times New Roman" size="3"> </font><p class="MsoNormal" style="margin: 0in 0in 0pt text-align: justify line-height: normal text-justify: inter-ideograph"><b><span style="font-family: "Times New Roman","serif" font-size: 12pt mso-bidi-language: FA">Background: </span></b><font size="3"><span style="font-family: "Times New Roman","serif"">Human
skin more than any other part of the body, is exposed to the risks of diseases
and complications of labor. One of the applications of study on the
relationship between skin and diseases is use of fingerprints in the diagnosis
and the subsequent treatment of it. We analyzed the fingerprint images of two
systematic diseases namely diabetes and addiction.</span><span style="font-size: 13pt mso-bidi-font-family: "B Mitra""><o:p /></span></font></p><font face="Times New Roman" size="3"> </font><p class="MsoNormal" style="margin: 0in 0in 0pt text-align: justify line-height: normal text-justify: inter-ideograph tab-stops: right 7.3pt center 265.9pt"><b><span style="font-family: "Times New Roman","serif" font-size: 12pt">Methods</span></b><span style="font-family: "Times New Roman","serif" font-size: 12pt">: The first
method has been used in the data analysis was power spectrum. The results
showed that in order to extract the features from fingerprint images other
methods must be found. The combination of textural features extracted from the
wavelet coefficients with the statistical features of wavelet, will make
stronger feature vector. In this thesis, two methods based on statistical
characteristics of wavelet and texture features of images have been used for
analysis of fingerprint images in patients.<span lang="AR-SA" dir="rtl"><o:p /></span></span></p><font face="Times New Roman" size="3"> </font><p class="MsoNormal" style="margin: 0in 0in 0pt text-align: justify line-height: normal text-justify: inter-ideograph tab-stops: right 7.3pt center 265.9pt"><b><span style="font-family: "Times New Roman","serif" font-size: 12pt">Results:</span></b><span style="font-size: 12pt mso-bidi-font-family: "B Mitra" mso-ascii-font-family: Calibri mso-hansi-font-family: Calibri"><font face="Calibri"> </font></span><span class="hps"><span style="font-family: "Times New Roman","serif" font-size: 12pt mso-bidi-font-family: Zar mso-ascii-theme-font: major-bidi mso-hansi-theme-font: major-bidi">Wavelet
transform and extracted features from wavelet coefficients act stronger than
the Fourier transform in image analysis. Combination of wavelet and texture
features had the best results. Results of addiction and diabetes test were 73%
and 67% respectively.</span></span><span style="font-family: "Times New Roman","serif" font-size: 12pt"><o:p /></span></p><font face="Times New Roman" size="3"> </font><p class="MsoNormal" style="margin: 0in 0in 0pt text-align: justify line-height: normal text-justify: inter-ideograph tab-stops: right 7.3pt center 265.9pt"><b><span style="font-family: "Times New Roman","serif" font-size: 12pt">Conclusions: </span></b><span class="hps"><span style="font-family: "Times New Roman","serif" font-size: 12pt mso-bidi-font-family: Zar mso-ascii-theme-font: major-bidi mso-hansi-theme-font: major-bidi">These results are promising in detecting relationship between fingerprints
with diseases. More research is needed on this topic.</span></span><span lang="AR-SA" style="font-family: "Times New Roman","serif" font-size: 12pt" dir="rtl"><o:p /></span></p><font face="Times New Roman" size="3"> </font>
اثر انگشت، بیماری، Power Spectrum، موجک، بافت.
Fingerprint, Diseases, Power spectrum, Wavelet, Texture.
49
57
http://rjms.iums.ac.ir/browse.php?a_code=A-10-1-1489&slc_lang=fa&sid=1
Saeideh
Yousefzadeh
سعیده
یوسف زاده
3900319475328460025052
3900319475328460025052
Yes
Shahrood University of Technology
دانشگاه صنعتی شاهرود
Morteza
Zahedi
مرتضی
زاهدی
3900319475328460025053
3900319475328460025053
No
Shahrood University of Technology
دانشگاه صنعتی شاهرود