Automated Detection of Red Lesions Using Superpixel Multichannel Multifeature

<div>Sensitivity versus <svg height="12.6199pt" id="M150" style="vertical-align:-3.38375pt" version="1.1" viewbox="-0.0498162 -9.23615 72.2374 12.6199" width="72.2374pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z" id="g113-50"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="480" vert-adv-y="480"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,9.145,0)"><path d="M535 230V280H52V230H535Z" id="g117-33"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="587" vert-adv-y="587"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,19.682,0)"><path d="M319 325C317 349 306 409 297 431C277 440 250 449 209 449C117 449 57 389 57 319C57 243 122 209 182 182C232 159 261 135 261 91C261 48 227 21 190 21C130 21 85 79 68 145L41 140C41 104 51 36 58 22C75 7 121 -12 172 -12C252 -12 337 35 337 126C337 195 286 231 210 262C166 281 126 304 126 348C126 388 152 417 191 417C240 417 274 378 294 318L319 325Z" id="g121-113"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="367" vert-adv-y="367"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,24.388,0)"><path d="M169 380V459C122 440 66 423 24 416V392C86 384 90 382 90 317V-135C90 -201 81 -207 17 -213V-240H253V-213C176 -207 169 -201 169 -125V6C182 -1 208 -11 238 -12C368 12 487 109 487 260C487 358 421 449 310 449C298 449 279 444 261 433L169 380ZM169 346C196 367 237 389 269 389C341 389 403 329 403 221C403 109 347 37 263 37C228 37 191 53 169 76V346Z" id="g121-110"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="524" vert-adv-y="524"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,31.317,0)"><path d="M380 106C343 72 306 56 265 56C195 56 116 112 115 248C235 252 361 262 377 265C396 269 400 277 400 297C400 374 333 449 250 449H249C198 449 144 421 103 376S37 269 37 201C37 88 109 -12 232 -12C263 -12 332 6 395 84L380 106ZM225 412C281 412 315 364 314 312C314 297 308 292 290 292C232 290 176 289 120 289C135 370 180 412 225 412Z" id="g121-99"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="425" vert-adv-y="425"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,36.907,0)"><path d="M390 111C344 68 312 56 269 56C212 56 118 102 118 241C118 346 175 401 241 401C277 401 312 388 342 360C350 352 355 349 361 349C372 349 394 371 394 392C394 403 391 411 378 422C362 436 329 449 288 449H287C250 449 190 432 138 392C71 341 37 274 37 197C37 90 112 -12 238 -12C297 -12 363 32 407 90L390 111Z" id="g121-97"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="423" vert-adv-y="423"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,42.406,0)"><path d="M135 536C164 536 186 560 186 587C186 617 164 639 136 639C109 639 85 617 85 587C85 560 109 536 135 536ZM252 0V26C188 32 181 38 181 106V451C138 433 90 420 39 412V388C99 379 102 374 102 312V106C102 38 95 32 32 26V0H252Z" id="g121-103"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="268" vert-adv-y="268"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,45.89,0)"><path d="M517 0V26C453 32 447 37 447 100V450C395 439 339 437 259 437H180V471C180 551 194 602 213 628C225 647 246 664 275 664C322 664 356 632 379 605C387 596 396 596 408 604C417 609 425 619 430 628C434 639 434 651 425 664C414 680 379 710 319 712C281 708 235 690 194 658C140 614 120 563 112 538C106 517 101 491 101 460V437H53L25 408L29 397H101V100C101 38 93 33 30 26V0H250V26C187 32 180 38 180 100V397H316C365 397 368 390 368 345V100C368 37 361 31 305 26V0H517Z" id="g121-27"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="535" vert-adv-y="535"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,52.846,0)"><path d="M390 111C344 68 312 56 269 56C212 56 118 102 118 241C118 346 175 401 241 401C277 401 312 388 342 360C350 352 355 349 361 349C372 349 394 371 394 392C394 403 391 411 378 422C362 436 329 449 288 449H287C250 449 190 432 138 392C71 341 37 274 37 197C37 90 112 -12 238 -12C297 -12 363 32 407 90L390 111Z" id="g121-97"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="423" vert-adv-y="423"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,58.344,0)"><path d="M135 536C164 536 186 560 186 587C186 617 164 639 136 639C109 639 85 617 85 587C85 560 109 536 135 536ZM252 0V26C188 32 181 38 181 106V451C138 433 90 420 39 412V388C99 379 102 374 102 312V106C102 38 95 32 32 26V0H252Z" id="g121-103"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="268" vert-adv-y="268"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,61.672,0)"><path d="M298 36L289 62C276 55 253 45 228 45C202 45 169 60 169 141V397H276C289 405 292 426 282 437H169V574L155 576L90 509V437H45L17 408L21 397H90V107C90 28 125 -12 188 -12C198 -12 213 -8 230 1L298 36Z" id="g121-114"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="305" vert-adv-y="305"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,65.676,0)"><path d="M478 437H297V411C355 404 361 392 349 355C329 292 285 174 257 106L167 356C153 394 158 404 205 411L204 437H2V411C57 404 66 391 88 336C117 265 162 144 202 30C208 13 209 0 204 -15C199 -28 191 -49 173 -84C149 -128 130 -153 98 -172C81 -184 73 -193 73 -209C73 -233 101 -257 129 -257C143 -257 156 -252 161 -232C175 -179 197 -122 264 38C333 203 364 286 390 339C417 395 425 403 478 411V437Z" id="g121-119"></path><glyph.data ascent="989" descent="-360" horiz-adv-x="459" vert-adv-y="459"></glyph.data></g></svg> curves with varied region sizes by applying two different classifiers.</div>

Computational and Mathematical Methods in Medicine

fig10

Figure 10

Figure 10: Automated Detection of Red Lesions Using Superpixel Multichannel Multifeature 