Lung Segmentation in 4D CT Volumes Based on Robust Active Shape Model Matching

<div>Comparison of segmentation results generated with methods <svg height="11.927pt" id="M141" style="vertical-align:-3.291101pt" version="1.1" viewbox="-0.0498162 -8.6359 24.1077 11.927" width="24.1077pt" 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="M962 650H795L470 145L347 650H176L170 622C268 613 275 606 244 503L190 322C150 188 132 126 118 91C102 50 80 33 18 28L12 0H245L251 28C175 35 170 48 174 93C177 128 191 180 220 284L292 542H294C331 392 383 150 409 4H432L774 555H776L714 137C700 40 694 34 612 28L606 0H868L874 28C793 34 784 37 797 137L849 533C859 612 863 616 956 622L962 650Z" id="g113-78"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="985" vert-adv-y="985"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,12.22,3.132)"><path d="M290 377C321 398 342 415 358 430C378 450 389 473 389 502C389 578 329 635 238 635H237C184 635 137 610 109 578L64 515L88 493C112 529 154 573 208 573S303 542 303 482C303 409 233 370 141 341L149 308C165 313 190 319 215 319C272 319 341 283 341 193C342 98 292 43 222 43C163 43 122 72 96 94C88 101 79 100 70 94C61 87 47 73 46 60C44 47 48 37 62 23C76 10 118 -12 165 -12C238 -12 430 62 430 223C430 297 379 359 290 375V377Z" id="g50-52"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="487" vert-adv-y="487"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,16.652,3.132)"><path d="M43 650V617C122 612 130 606 130 522V128C130 44 122 37 34 32V0H275C400 0 497 25 573 82C652 142 698 229 698 350C698 445 662 518 613 565C549 625 456 650 327 650H43ZM217 544C217 580 220 591 229 599C240 607 264 613 311 613C380 613 437 599 482 570C561 523 598 436 598 336C598 177 511 40 324 40C248 40 217 61 217 135V544Z" id="g58-66"></path><glyph.data ascent="1007" descent="-369" horiz-adv-x="744" vert-adv-y="744"></glyph.data></g></svg> and <svg height="11.8174pt" id="M142" style="vertical-align:-3.1815pt" version="1.1" viewbox="-0.0498162 -8.6359 24.1077 11.8174" width="24.1077pt" 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="M962 650H795L470 145L347 650H176L170 622C268 613 275 606 244 503L190 322C150 188 132 126 118 91C102 50 80 33 18 28L12 0H245L251 28C175 35 170 48 174 93C177 128 191 180 220 284L292 542H294C331 392 383 150 409 4H432L774 555H776L714 137C700 40 694 34 612 28L606 0H868L874 28C793 34 784 37 797 137L849 533C859 612 863 616 956 622L962 650Z" id="g113-78"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="985" vert-adv-y="985"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,12.22,3.132)"><path d="M462 177V227H365V632H320C217 496 116 350 21 208V177H284V109C284 43 280 38 190 31V0H451V31C369 38 365 43 365 108V177H462ZM284 227H88C155 336 218 430 282 519H284V227Z" id="g50-53"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="487" vert-adv-y="487"></glyph.data></g><g transform="matrix(.0091,0,0,-0.0091,16.652,3.132)"><path d="M43 650V617C122 612 130 606 130 522V128C130 44 122 37 34 32V0H275C400 0 497 25 573 82C652 142 698 229 698 350C698 445 662 518 613 565C549 625 456 650 327 650H43ZM217 544C217 580 220 591 229 599C240 607 264 613 311 613C380 613 437 599 482 570C561 523 598 436 598 336C598 177 511 40 324 40C248 40 217 61 217 135V544Z" id="g58-66"></path><glyph.data ascent="1007" descent="-369" horiz-adv-x="744" vert-adv-y="744"></glyph.data></g></svg>. Coronal CT cross sections with marked lung boundaries in combination with corresponding 3D lung mesh models are shown to enable locating and assessing segmentation errors as well as differences between results.</div>

International Journal of Biomedical Imaging

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Figure 5

Figure 5: Lung Segmentation in 4D CT Volumes Based on Robust Active Shape Model Matching 