Dermatology 2013

Notes: Spiewak, Radoslaw

eng

Research Support, Non-U.S. Gov’t

Croatia

2014/01/31 06:00

Acta Dermatovenerol Croat. 2013 Dec;21(4):230-5.

URL: http://www.ncbi.nlm.nih.gov/pubmed/24476609

Author Address: Prof. Radoslaw Spiewak, MD, PhD, Department of Experimental Dermatology and Cosmetology, Faculty of Pharmacy, Jagiellonian University ul. Medyczna 9, 30-688 Krakow, Poland; spiewak.eu@gmail.com.

 

 

Reference Type:  Journal Article

Record Number: 4561Author: Spyridonos, P., Gaitanis, G., Bassukas, I. D. and Tzaphlidou, M.

Year: 2013

Title: Gray Hausdorff distance measure for medical image comparison in dermatology: Evaluation of treatment effectiveness by image similarity

Journal: Skin Res Technol

Volume: 19

Issue: 1

Pages: e498-506

Date: Feb

Short Title: Gray Hausdorff distance measure for medical image comparison in dermatology: Evaluation of treatment effectiveness by image similarity

Alternate Journal: Skin research and technology : official journal of International Society for Bioengineering and the Skin

ISSN: 1600-0846 (Electronic)

0909-752X (Linking)

DOI: 10.1111/srt.12001

Accession Number: 23020792

Keywords: Algorithms

Combined Modality Therapy

Disease Progression

Drug Monitoring/methods

Hospitalization

Humans

Image Processing, Computer-Assisted/*methods

*Models, Biological

Pattern Recognition, Automated/*methods

Photography/*methods

Severity of Illness Index

Stevens-Johnson Syndrome/*pathology/*therapy

Treatment Outcome

Abstract: INTRODUCTION: In clinical dermatology, the stabilization of the overall skin condition can be in many cases the earliest qualitative measure of the effectiveness of the therapeutic intervention. Subjective image comparisons, that offer empirical ‘qualitative’ judgments of degrees of image similarities, are traditionally employed by the involved physicians. OBJECTIVES: To quantify, by means of an image similarity metric, the degree of stabilization of an expanding skin disease, and to identify the situation of ‘no further change’ of the skin condition of the patient, providing thus the physician with an early, objective measure of the efficacy of the used therapy. METHODS: For treatment assessment, a variant of gray Hausdorff distance metric was employed to compare images of lesional skin segments of a patient, taken at different time points during a therapeutic course. Prior to image comparison, an effective preprocessing scheme was adapted to constrain wide pose and light variations. The proposed similarity algorithm was tested on raw clinical image data sets of patients diagnosed with toxic epidermal necrolysis, a life-threatening condition with rapid evolution. Fine tuning of algorithm’s parameters was optimized using Precision-Recall curves. RESULTS: Proposed image comparison method resulted in a high-degree of image similarity (about 96%) between pictures taken at second and fifth day of hospitalization. Current similarity results substantiate a significant agreement between the computer-treatment assessment, by means of image comparison, and the corresponding clinical experts’ review of skin condition. CONCLUSION: Objective evidence of ‘no further change’ situation may provide (a) intuitive clinical decision support to dermatologists in assessing aggressive skin conditions, where the timely evaluation of treatment response is of vital importance and (b) a versatile end-point measure for corresponding therapeutic clinical trials.

Pages: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295