Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2724009pt" id="M1" height="11.8957pt" version="1.1" viewBox="-0.0657574 -11.6233 11.7924 11.8957" width="11.7924pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g50-68" d="M690 629C653 643 577 667 483 667C225 667 24 528 24 292C24 92 174 -17 367 -17C448 -17 534 1 570 10C592 34 642 131 658 174C648 180 639 186 629 192C562 89 499 21 382 21C223 21 130 138 130 298C130 467 255 627 462 627C582 627 643 589 650 462L686 466C689 517 688 580 690 629Z"/></g></svg>-Means Clustering

<table class="table-group" id="tab4"><tr><td><table class="table"><tr><td class="thead-hr" colspan="10"><hr/></td></tr><tr class="thead"><td align="left">Image</td><td align="center">Measure</td><td align="center">GKFCM1</td><td align="center">GKFCM2</td><td align="center">FLICM</td><td align="center">KWFLICM</td><td align="center">MICO</td><td align="center">ARKFCM<sub>1</sub></td><td align="center">ARKFCM<sub>2</sub></td><td align="center"><span style="width: 61.2405ptpx;"><svg height="11.8487pt" id="M181" style="vertical-align:-3.160609pt" version="1.1" viewbox="-0.0498162 -8.68809 61.2405 11.8487" width="61.2405pt" 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="M682 0V33C615 38 603 49 571 134C507 305 441 494 378 665L343 655L136 136C101 48 86 41 22 33V0H246V33C170 41 161 50 183 112C196 152 209 192 224 232H441C461 176 478 126 493 87C504 49 499 41 433 33V0H682ZM425 279H242C273 363 303 448 335 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353 216 348V518C216 605 226 612 305 617V650H40V617C123 612 130 605 130 518V131C130 46 121 38 44 33V0H310V33C226 38 216 46 216 131V318C235 322 249 319 274 290C367 181 444 84 520 0H676Z" id="g58-73"></path><glyph.data ascent="1007" descent="-369" horiz-adv-x="685" vert-adv-y="685"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,26.351,0)"><path d="M502 500C497 551 492 613 491 650H43V617C122 612 130 606 130 521V129C130 45 122 38 41 33V0H319V33C227 38 217 45 217 129V305H319C411 305 413 295 427 225H461V421H427C414 357 411 348 319 348H217V580C217 609 219 612 250 612H330C401 612 423 605 439 578C452 557 458 539 467 496L502 500Z" id="g58-68"></path><glyph.data ascent="1007" descent="-369" horiz-adv-x="540" vert-adv-y="540"></glyph.data></g><g transform="matrix(.013,0,0,-0.013,33.371,0)"><path d="M618 181C565 77 513 26 413 26C264 26 151 150 151 336C151 486 240 625 407 625C516 625 573 582 600 475L634 483C627 540 622 581 613 638C585 643 518 665 435 665C211 665 46 526 46 315C46 158 157 -15 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358 208 385 208 407C208 433 201 451 176 451C124 451 64 404 24 348L44 320C86 366 113 382 121 382C126 382 128 381 128 374C128 368 126 356 122 341C102 266 88 204 81 164C77 143 73 121 73 107C73 23 131 -12 187 -12C234 -12 281 10 322 45C343 5 383 -12 422 -12C559 -12 698 174 698 334Z" id="g50-120"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="722" vert-adv-y="722"></glyph.data></g></svg></span></td></tr><tr><td class="thead-hr" colspan="10"><hr/></td></tr><tr><td align="left" rowspan="2">Brats1</td><td align="center"><i>E</i></td><td align="center">1.311</td><td align="center">1.288</td><td align="center">1.392</td><td align="center">1.424</td><td align="center">1.309</td><td align="center"><b>1.274</b></td><td align="center"><b>1.270</b></td><td align="center"><b>1.279</b></td></tr><tr><td align="center">Time (s)</td><td align="center">2.591</td><td align="center">1.516</td><td align="center">9.510</td><td align="center">635.413</td><td align="center">1.747</td><td align="center"><b>1.185</b></td><td align="center"><b>1.111</b></td><td align="center"><b>1.272</b></td></tr><tr><td align="center" colspan="10"><hr/></td></tr><tr><td align="left" rowspan="2">Brats2</td><td align="center"><i>E</i></td><td align="center">1.307</td><td align="center">1.297</td><td align="center">1.336</td><td align="center">1.340</td><td align="center">1.298</td><td align="center"><b>1.273</b></td><td align="center"><b>1.271</b></td><td align="center"><b>1.279</b></td></tr><tr><td align="center">Time (s)</td><td align="center">1.576</td><td align="center">1.115</td><td align="center">5.170</td><td align="center">400.295</td><td align="center">1.546</td><td align="center"><b>1.091</b></td><td align="center"><b>0.827</b></td><td align="center"><b>0.975</b></td></tr><tr class="table-tr"><td colspan="10"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Segmentation performance measure <svg height="8.64656pt" id="M180" style="vertical-align:-0.04981995pt" version="1.1" viewbox="-0.0498162 -8.59674 8.229 8.64656" width="8.229pt" 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="M615 650H141L132 618C223 612 227 607 212 526L136 123C122 42 112 38 27 32L18 0H522C539 33 580 135 592 166L558 179C536 139 512 100 486 75C454 48 420 41 345 41C287 41 252 42 237 55C221 68 220 100 231 158L261 316H357C455 316 455 309 455 235H489L529 437H494C468 366 460 360 369 360H269L305 565C315 609 316 611 357 611H450C525 611 535 599 548 578C559 556 561 526 560 482L595 486L615 650Z" id="g50-70"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="639" vert-adv-y="639"></glyph.data></g></svg> and running time on the Brats1 and Brats2 images.

Computational and Mathematical Methods in Medicine

tab4

Table 4

Table 4: Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.2724009pt" id="M1" height="11.8957pt" version="1.1" viewBox="-0.0657574 -11.6233 11.7924 11.8957" width="11.7924pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g50-68" d="M690 629C653 643 577 667 483 667C225 667 24 528 24 292C24 92 174 -17 367 -17C448 -17 534 1 570 10C592 34 642 131 658 174C648 180 639 186 629 192C562 89 499 21 382 21C223 21 130 138 130 298C130 467 255 627 462 627C582 627 643 589 650 462L686 466C689 517 688 580 690 629Z"/></g></svg>-Means Clustering 

Computational and Mathematical Methods in Medicine

Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy -Means Clustering

Table 4