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limited res nce it brea classifying rocessing o

ure 3.6 A Po

at one perce used for reg which is 99 mean value

d is then up t in the le

cking

olution, dis aks, the reg g those vox one. It is so

ossible brok

entage of co gion growin

9%.

of classifie pdated. It m

akage, and

stal bronchi gion growin xels with low

called leak

ken airway

onfidence in ng is the me

ed region i means the th d the small

wall are so ng procedu w intensity age or expl

wall.

nterval is th ean value m

is recalculat hreshold hav

er one wil

ometimes br ure previou

in the alve osion into l

he most su multiplied by

ated as show ve 1% toler ll result in

roken after usly describ eoli or bron lung. As a r

itable y one

wn in rance.

poor

(3-5)

some bed is

nchus result,

it is show

entire fill u reach there airwa

occu gettin

the le the a lung.

regio and q regio grow

difficult to wed in figure

There are t e image. It up the entir h lower ord e will be fe

ay.

Therefore, urred, and pr

ng the best The leakag eakage occu airway is dis

.

In this wo on with a sp quantities h on is detect wing process

o identify th e 3.6.

two ways to makes the a re airway lu er bronchi.

ewer chanc

the region revents the one before ge can be de

urred, the v stributed in

ork, leakag pecific thres how dramati ted as equa s.

hose lower

o deal with t airway wall umen, mak Another wa ces to leak

growing pr threshold b leakage.

etected by m olume incre

a small ran

e detection shold volum ically it gro ation 3-6, a

order bron

this issue. O l linked, bu king the reg

ay is to low into lung,

rocedure ha becoming to

monitoring eased drama nge, and ther

n is implem me. It tries to wn. If an ex a leakage is

nchi. A poss

One is to sm ut loses prec

gion growin wer the thres

but still n

s to make s oo high. Fal

the volume atically. The refore it is e

mented by o catch the g

xponential v s identified,

sible broken

mooth or to cession. It is ng procedur shold. With

o chance to

sure that the lling back th

e of classifi e intensity o easy to expl

monitoring growth of c volume gro , and then

n airway w

downsamp s also possib

re impossib lower thres to identify

ere is no lea the threshol

fied region.

of voxels ou lode to the e

g the segm classified vo owth of clas

stops the r wall is

le the ble to ble to shold,

distal

akage d and

Once utside entire

mented olume sified region

(3-6)

3.4

boun segm fragm

morp visua

Postpr

Any tissue ndaries and mented airw

ments.

In order t phology clo al effect and

rocessin

e in the nat d surfaces.

way that p

to reconstru osing operat

d reasonable

ng

ture world Airway is produced by

uct the bou or is applie e segmentat

is rarely to s an organ

y previous

undary of ed. After app

tion.

o be seen w with smo s procedure

airway wa plying this

with sharp o ooth surface es may ha

all and fulf operator, it

or zigzag e e likewise.

ave corners

fill the cav would get b

edges, . The s and

vities, better

Ch

ne-based tra ch points ar Though the this measur the mappin The airway the shape larity of the ndmarks.

In order to ts. Forming ch points is ance within

tion which i In this wor s by Thin-P aust search,

ementation It is an imp tion is prop k, the best

duced. It tr

er 4 L

to overcom ansformation

re used to m e similarity

rement. It i ng of gray v y branch poi

of lung w e airway bifu

take the ad g the landm s the way to n landmark is going to b rk, it adopts

Plate-Spline , and stops of image re portant issu posed for th

weighting ries to find t

Lung

me the la n is used to matching the measure is gnores the p value, and ca

ints are ado will be. The furcates. The

dvantage of marks as a

o take bran sets could be minimize s the method e transform s at a pre egistration, e of the com he sake of k

of similar the best sui

Regis

ack of inte o solve the i e structure o used by de physical me ausing the r opted as land e airway is erefore, airw

the local str measureme nch points a d be consid

ed.

d Li et al. p mation [6, 2 defined am but loses ef mbination o keeping bot rity measur it weighting

strati

er-subjects inconsistent of lungs.

fault, it is n eaning of im registration

dmarks, bec the inner way branch

ructure, it h ent in beha as a cost fu

dered as a

proposed w 28]. It mini mount of it

fficient.

of both mea th advantag re and land g by trial an

ion

human lu t shape info

not sufficien mage presen

become me cause the ai structure o points have

has to take u alf of the q unction. Thu measurem

hich tries to imizes all m terations. I

asurements.

ges of each dmark dista nd error, and

ung registr ormation; ai

nt to register nted. It cons eaningless.

irway determ of lungs. It

e to be iden

use of the b quantificatio us, the Eucl ment of the

o register h measureme It is a com

A weighted measure. In ance measu d trying to f

ation, irway

r with siders

mines exist ntified

ranch on of lidian e cost

robu

st weighting

Branch

To take use airway branc In the prev y for a dire cting a voxe The proced etail.

.1 Airwa

The airway tunnel. The le point repr In order to rithm is in n

The thinnin el wide struc

ch point.

The reason essing time ning proced verable. If a

g with good

h Point

e of the bra ching must vious work ect usage. B el represent dures of col

ay Thinn

y segmented e cross secti resent the b o retrieve need [30]. It ng procedu cture, to eas

n not to app e. A postpr dure may b a branch is m

d performan

Sets

anch point s be identifie in chapter Because the as the branc llecting bran

ning

d, is a tree-l ion of the ai ranch point the medial t helps the o ure is to pro

se the diffic

ply pruning rocessing lik better help

miss-pruned nce.

set which re ed.

3, the airw e airway is ch point is a nch points a

like structur irway is a f t [31].

l line of th operator get

oduce a sk culty of retr

algorithms ke morpho than prunin d, a branch

epresent the

ay is succe a tree-like an issue nee are describe

re. There ar flat lumen, s

he airway, tting the ind eleton of th rieving a sin

after thinni logy closin ng, because

point will b

inner struc

ssfully segm air tunnels, eds to overc ed in the fo

re airway w so that it is d

a thinning dex of the br

he airway.

ngle point th

ing procedu ng or smoo e the pruni be lost.

cture of the

mented. It i , the decisi come.

ollowing sec

wall and lum difficult to f

g / skeleton ranch point

It will be a that represen

ure is to sav oth filters b ing result i

lung,

is not on of

ctions

men in find a

nizing . a one nt the

ve the before is not

contr

In this wor ributed this -review

on-.2 Branc

Branch po ge now is a erse the air S).

Mori et al.

ne thing ha e and unwan e [25].

In this wor ility.

.3 Branc

There are l the major b Twenty-thr y are locate chus, right chus 4 + 5, chus 10. On

rk, the meth implement line publica

ch Points

ints are ea a skeleton o rway tree. I

proposed a as to consid nted false b

rk, the branc

ch Point

ots of bifur branch poin ree branch p ed at trache

bronchus 1 right bronc n the other

od Homann ation to the ation in med

s Identifi

asy to ident of the airw It can be B

an automatic der, the airw branching [6

ch points ar

Sets Ma

cations in th ts are consi points with

a or carina , right bron chus 7 + 8, side, they

n et al. prop e Insight Jou

dical image

fication

tify manual way. All the

Breadth-firs

c branch po way might 60], so that

re identified

atching

he airway. I idered.

low branch , right main nchus 3, righ right bronc are located

posed is ado urnal which processing

lly. After t e identificat st search (B

oint retrievin be miss-seg Tschirren e

d manually

In order to f

hing order a n bronchus ht intermed chus 9 + 10 d at left mai

opted. Homa h is an open and visuali

he thinning ion procedu BFS) or De

ng algorithm gmented. It et al. tried t

on purpose

find commo

are selected , 1st divisio diate, right b , right bron in bronchus

ann et al. al access and ization [16]

g procedure ure has to epth-first s

m [29]. But t causes loo to overcom

e of accurac

on branch p

for recogn on of right bronchus 6, nchus 9 and s, 1st divisi

ready d open

.

e, the do is search

there

left m 6, lef

may there

4.2

regis align comp

and t comp

equa

and r

main bronch ft basal, left

In this wor be encoun e are still roo

Prereg

In order t stration is a ned, preregi putational e In this wor translations putational r There are ation 4-1.

The rigid-b rotation tran

hus, left upp t bronchus 8 rk, the airwa ntered in pr oms for refi

gistratio

to speed up a time consu istration re expense.

rk, a rigid-b . It is one o esources.

six param

body transfo nsform matr

per division 8, left bronc ay branch p revious pro ine as ment

on

p the entir uming imag educes time

body transfo of the simpl

meters to de

orm matrix i rix, where

T







n, left lingu chus 9 + 10, oint sets are ocedures. Th

tioned in pre

re process, ge processi e spent by

ormation is lest transfor

escribe the

M TR

is equal to c

1 0 0

0 1 0

0 0 1

0 0 0

ular division , left bronch e matched m hough auto evious secti

a preregis ing techniqu

the later

employed.

rmations tho

rigid-body

combining t

1 2

3

1 q q q







n, left inferi hus 9 and le manually, co omatic algo

ion.

stration is ue. If imag

registration

It consists o ose do not r

y transform

translation t

ior, left bron eft bronchus

onsidering e orithms do

adopted. I ges have rou n which is

of only rota require too

mation matr

transform m nchus s 10.

errors exist,

Image ughly high

ations much

rix as

(4-1)

matrix

(4-2)

and

R







4.3

propo rema facto adde

 

4

1 0

0 cos 0 sin

0 0

q q



 



Registr

The propos osed [42], ain the sam ors those ar

d because it

 

 

4 4

4 4

0 sin cos 0

q

q q

ration A

sed method the compo me as const re different

t is required

Figure 4.1 Ima

 

4

0 cos 0

0 sin 1







 

 

Architec

is designed nents, mult traints and from the c d by the cor

1 The Multi age is retrie

 

 

5

5

s 0

0 1

n 0

0 0

q

q

cture

d in order to ti-resolution

fixed facto competing m rresponding

i-resolution eved from th

 

 

5

5

sin 0

0 0

cos 0

0 1

q

q

o compete w n pyramid, ors. The co

method. On cost functi

registration he ITK man

   

66

0 cos 0 sin

0 0

0 q

q

  

  

  

with the met optimizer ost function ne of the tra

on.

n approach.

nual.

  

  

66

sin cos 0 0 q q

thod Staring and interpo ns are contr

ansformatio 0 0 0 0 1 0 0 1





 (4-3)

g et al.

olator rolled ons is

4.3.

that r entire

imag user 4.2.

4.3.

way

Non-landm param

.1

Multi-In this wor registering f e registratio A Gaussian ge is blurred specific py

.2 Transf

Betke et al [37]. Now -rigid transf

According mark-based meters. Onl

Figure 4.2 Ima

-Resolut

rk, a multi-r from low re on as shown n blur filter d then subs yramid level

form

l. proposed wadays, rig

formation is to the me d registratio ly source an

The multi-r age is retrie

tion

resolution a esolution to n in figure 4 r is used to

ampled to a l reached. A

a lung rigi gid registrat

s in need.

ethod Rex on [40]. T nd target lan

resolution r eved from th

approach is original res 4.1.

build the m a lower lev A multi-reso

id registrati tion is not

Cheung et PS transfo ndmarks ar

registration he ITK man

adopted. It solution for

multi-resolu el pyramid.

olution fram

ion using It t good eno

t al. propos ormation do re required.

framework nual.

t is a coarse r the sake of

ution pyram . Repeating mework is s

terative Clo ough for lu

sed, TPS i oes not req

Therefore, k.

e to fine m f speeding u

mid. The ori g this step u showed in f

osest Point ung registr

is just fitte quire too there is no

ethod up the

iginal until a figure

(ICP) ation.

ed for many need

to fin

and A

trans regis it is n in eq

4.3.

It is adap AGS

4.3.

local

ne tune any In this wor Arbel propo

A postregi sformation.

stration puts necessary to quation 4-5.

.3 Optim

In this wor a stochast tive step si SD has an ad

.4 Interp

Trilinear in l axial data o

It is a fa

parameters rk, the TPS osed [39, 47

istration is It is becau s both image

o adopt B-S

mizer

k, Adaptive tic gradient ize predicti daptive step

polator

nterpolation on lattice po ast algorith

s.

implement 7]. The trans

required se that the es on finite Spline regist

e Stochastic t descent o ion. In con p size which

n is used in oints.

hm with lo

tation is bas sformation i

to fitting TPS only t grid which tration to m

c Gradient D optimization ntrast to Re h helps the c

n this work.

ow comput

sed on the m is illustrated

the shape tries to mat

is denser th match the bo

Descent (AS n method f egular Step

convergent

. It approxi

tational co

method Dav d in equatio

informatio ch the land han landmar oundary. B-S

SGD) optim for image r Gradient D speed faster

imates the v

mplexity a

vis et al., B on 4-4.

on by B-S dmarks. B-S rks. As the Spline is sh

mizer is used registration Decent (RS r than ever.

value withi

against B-s rooks

(4-4)

Spline Spline result, howed

(4-5)

d [51].

with SGD),

in the

spline

interp interp but p

4.3.

contr and l

withi meas

wher

dista struc landm

weig

polation an polated vox produces bet

.5 Cost F

The cost fu ribution is t landmark di The simila in images.

sure in this w

re Ω is the The landm ance of two cture matche

marks.

The goal o ghting. A we

nd window xels. It is a tter result.

Function

unction is th to provide a istance mea arity measur

Mean of S work. The M

MSD T

lung region mark distanc o point set ed. It compu

LDM

of this thes eighted cost

ed sinc int little bit sl

n

he most im a practical asure.

re is shown Squared Di MSD is defi

; ,

n and μ is t ce is showe s with kno utes the dist

M T ; ,

sis is to me t function is

terpolation, lower than

mportant and weighting f

n in equatio ifferences ( fined as,

Ω

the instance ed in equat own corresp

tance from

erge two m s shown in e

and result Nearest Ne

d the core p for combini

on 4-6. It i MSD) is e

e of transfor tion 4-7. It pondence.

target landm

x T x

measuremen equation 4-8

ts enough eighbor (NN

part of this t ing both sim

s the gray mployed fo

rmation.

t is aimed t It makes t marks to tra

nts as a cos 8,

good quali N) Interpol

thesis. The milarity me

value diffe or the simi

to minimiz the local ai ansformed s

st function ity of

ation,

main easure

erence ilarity

(4-6)

ze the irway ource

(4-7)

by a

wher respe

disco avail imag be di

coeff

re C is the ectively. Ea The cost fu

C

While norm overed. The lable in DIC ges are matc istributed ne In this case ficient is im

C T

e weighted ch is arr unction can

T ; I , I

malizing th e maximum COM, and th

ched. There ear zero. Th e, cost func mplicit and ta

T ; I , I

cost functi ranged with be expande

ω Ω

ω ∑

he measure m of MSD he minimum efore, the sim he LDM is s

tions are w aken place b

ion, and h a weightin ed as equatio

1

Ω

x T

ements, the is equal to m is zero. A milarity is h similar to M weighted wit

by weightin

ω c T ; I

and are ng for to

on 4-9.

T x

maximum o square of After perform

high. If the MSD.

thout norma ng directly.

, I

e target and otal N equal

m and minim f twice max ming image

MSD is no

alization. Th

d source im al to two.

mum shou ximum inte e registratio ormalized, i

he normaliz (4-8)

mages

(4-9)

ld be ensity

n, the it will

zation

Ch

In this chap e time.

All of the 3 GHz proc ght Toolkit ( essing [55].

on Microsof The registr ce software to deal w ix. A modif lastix. The c 5. A bug was Images are ges, and des tal Imaging versity Hosp

loyed.

Volumes ar [9, 53, 54]

master thes

er 5 E

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