1 SEGMENTATION OF BREAST TUMOR IN THREE- DIMENSIONAL ULTRASOUND IMAGES USING THREE- DIMENSIONAL...

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SEGMENTATION OF BREAST TUMOR IN THREE-DIMENSIONAL ULTRASOUND IMAGES USING THREE-DIMENSIONAL DISCRETE ACTIVE CONTOUR MODEL

Ultrasound in Med. & Biol., Vol. 29, No. 11, 2003

資訊所 P76994458 石慧萱 2011.01.06

HCI Final Report

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Outline

• Introduction

• Materials And Methods– Review– Proposed 3-D Segmentation

Method

• Result

• Conclusion

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Introduction

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Introduction

• Clinically, ultrasound is widely used for tumor detection. Although the artificial recognition method is good, manual handling several hundreds of images in a 3-D data set is a time-consuming process.

• Precise 3-D segmentation approach can provide an accurate evaluation of the tumor volume and solid tumor shape

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Introduction

• In this paper, we apply three-dimensional active contour model to a 3-D ultrasonic data file for segmenting of the breast tumor

• However, there is emphasis on these 3-D techniques that they do not consist of a series of 2-D techniques.

• When they work, they will consider the horizontal, vertical and depth directions at the same time.

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Introduction

• The ultrasound imaging has some characteristics including noise, speckle and tissue-related textures.

• The conventional edge-based image segmentation and region-based segmentation are not suited to find tumor boundaries.

• Stick is a boundary detection approach based on an image enhancement technique.

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Introduction

• We propose a new 3-D active contour model based on the traditional 2-D snake to find the 3-D shape in a 3-D US data set.

• The 3-D active contour model will make the initial contour approach to the real contour of the tumor.

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Intoduction

Extract 3D volume data

3D stick procedure

Apply the auto threshold method to obtain the binary image

Apply the 3D morphological process (close & opening)

to obtain the initial 3D shape of the tumor

3D snake procedure

Final 3D shape of the tumor

Initial Shape Finding Final Shape Deformation

Flow Chart of the Proposed Method

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Introduction

• The use of these 3-D techniques not only segments the 3-D shape but also obtains the volume of the tumor.

• The volume of the tumor calculated by the proposed method will be compared with the volume calculated by the software with the physician’s manually drawn shape.

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Review

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3-D Breast US

• In this work, the 3-D sonography was performed using a Voluson 530D (Kretz Technik, Austria)scanner and a Voluson small part transducer S-VNW5 to 10.

• A linear-array transducer with a frequency 5 to 10 MHz, a scan width of 40 mm and the sweep angle of 20° to 30°

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3-D Breast US

• These 3-D volume file should be saved in Cartesian coordinates by the Voluson 530D or 3-D View 2000 program

• Three planes of a volume data set could be obtained by using our developed program– Longitudinal

– Transverse

– Coronal planes

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Reviews of Stick

• Using line segments (also called sticks) in different angular orientations as a template

• Large-scale linear features line up with sticks of adequately short length, while speckle does not if the sticks are long enough

• Select the most suitable orientation at each point

• To reduce speckle and improve edge information in ultrasonic images

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Reviews of Stick

• A square N x N area in an image

• 2N - 2 short lines that pass through the central pixel,with each line including exactly N pixels

• Calculate the average of pixel values along the line , select the maximum average as the value of center pixel

5x5 area2*5 -2=8組 stick

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Reviews of Snake

• An established method for the contour extraction and image interpretation

• The contour is represented as a set of vertices that move in response to:– Internal forces :

derived from the properties of the shape of the contour,minimize the local contour curvature

– External forces : derived from the image features, make the model follow a path of low energy through the external energy distribution

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Reviews of Snake

• The deformation process:

• The forces acting on a vertex xi are internal, external and damping forces

• wint, wext and wdamp are the weighting factors, vi is the velocity of vertex xi

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Proposed 3-D segmentation method

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Flow Chart

Extract 3D volume data

3D stick procedure

Apply the auto threshold method to obtain the binary image

Apply the 3D morphological process (close & opening)

to obtain the initial 3D shape of the tumor

3D snake procedure

Final 3D shape of the tumor

Initial Shape Finding Final Shape Deformation

Flow Chart of the Proposed Method

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3-D Stick

• Two kinds of stick length, five and seven, are used in the proposed 3-D stick

• Calculated based on the symmetry

• Defined based on how many stick elements are included in one frame

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3-D Stick

Length = 5 , b (1 – 3 -1 )

x

z

y

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3-D Stick

Two sample forms in (a) category a, and (b) category b of the stick with length five

Two sample forms in (a) category a, (b) category b and (c) category c of the stick with length seven.

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Flow Chart

Extract 3D volume data

3D stick procedure

Apply the auto threshold method to obtain the binary image

Apply the 3D morphological process (close & opening)

to obtain the initial 3D shape of the tumor

3D snake procedure

Final 3D shape of the tumor

Initial Shape Finding Final Shape Deformation

Flow Chart of the Proposed Method

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Automatic Thresholding

• Minimize the sum-of-square errors SSE(t) between the gray values and the mean values

and hi is the number of pixels with gray level i.

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Flow Chart

Extract 3D volume data

3D stick procedure

Apply the auto threshold method to obtain the binary image

Apply the 3D morphological process (close & opening)

to obtain the initial 3D shape of the tumor

3D snake procedure

Final 3D shape of the tumor

Initial Shape Finding Final Shape Deformation

Flow Chart of the Proposed Method

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3D Morphology

• Use morphologic techniques– Opening : erosion + dilation– Closing : dilation + erosion

• Extend the morphologic operations from 2-D to 3-D use a 5x5x5 cube in the 3-D morphologic filtering

• Use a 5x5 square for morphologic edge detection

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Flow Chart

Extract 3D volume data

3D stick procedure

Apply the auto threshold method to obtain the binary image

Apply the 3D morphological process (close & opening)

to obtain the initial 3D shape of the tumor

3D snake procedure

Final 3D shape of the tumor

Initial Shape Finding Final Shape Deformation

Flow Chart of the Proposed Method

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3D Snake- Internal Force

• The proposed 3-D snake model modifies the internal forces and the external forces to the form of 3-D

• Internal forces are related with the local contour curvature

• Besides the curvatures of the horizontal and vertical directions, the internal forces also calculate the curvature of the depth direction

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3D Snake- Internal Force

• The local curvature ci at xi :

Xi

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3D Snake- Internal Force

• The locally tangential unit vector at a vertex Xi :

• The locally tangential unit vector at a vertex

Xi

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3D Snake- Internal Force

• The unit vector in the local radial orientation is derived from by a rotation over π/2 radians:

Xi

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3D Snake- Internal Force

• The internal force fint,i can be defined as :

(8)

(9)

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3D Snake- External Force

• In the conventional snake model, the external force is usually calculated from the gradient of the original image

• The proposed external force is calculated from the texture information

• The Gaussian blurring is applied for better results• The original image feature is also used to retain the

boundary information

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3D Snake- External Force

• I(x,y,z): the original image• T(x,y,z): the texture image after applying the

texture analysis to I• Texture analysis: calculate the average variance of

the voxel, centered at point P(x,y,z), with the size of 3x3x3 pixels

• TGB(x,y,z) : the Gaussian blurring operator is applied to the texture image T(x,y,z)

• -I’ and –TGB’ : derived from normalizing -I and -TGB into [0,1].

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3D Snake- External Force

• The external energy distribution E is defined as the sum of –I’ and –T’GB, and the external force fext can be calculated from E

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3D Snake-Deformation Process

• t : the step at a particular time t

• ∆t: the incremental time

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3D Snake- Deformation Process

• The distance between two vertices will change constantly

• Periodically resampling the model along its path: – The segment length > upper bound– The segment length < lower bound

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Calculation of Volume of Tumor

• The region-growing method can be used to fill up the region encircled by the final shape

• Volume: The number of voxels in the filled regions

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Result

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Data

Benign

Malignant

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Resulting Images

(a) The original image.(b) The equalized image of (a)(c) The stick image of (b)(d) The image after automatic threshold of (c)(e) The image after morphologic process of (d)(f) The contour of the tumor derived from (e)(g) The result of the snake

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Resulting Images

(a) The original image.(b) The equalized image of (a)(c) The stick image of (b)(d) The image after automatic threshold of (c)(e) The image after morphologic process of (d)(f) The contour of the tumor derived from (e)(g) The result of the snake

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Resulting Images

(a) The original image.(b) The equalized image of (a)(c) The stick image of (b)(d) The image after automatic threshold of (c)(e) The image after morphologic process of (d)(f) The contour of the tumor derived from (e)(g) The result of the snake

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Resulting Images

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Expert Annotation

• The VOCALTM software contained in the 3-D VIEWTM is a tool for calculating the volume data as well as the geometric surface information in a well-defined border lesion

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Comparison

• The average match rate is about 95%

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Performance

Morphology

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Conclusion

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Conclusion

• The 3-D techniques, including the 3-D stick, 3-D morphologic process and 3-D snake model, are first used and the outcome is similar to that of the VOCALTM software with the physician’s manual adjustment

• The extension of the traditional 2-D segmentation approach and the use of the depth information between image slices make the segmentation result more precise

• The introduced 3-D ultrasound segmentation method not only provides the accurate segmentation of the tumor shape, but also evaluates the volume of the tumor.

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Conclusion

• Physician does not need to spend a lot of time manually drawing the initial contour in each ultrasonic image of the tumor

• The obtained final 3-D shape of the tumor can be separated into the contours in image slices and these contours can be treated as the 2-D segmentation result of each ultrasonic image of the tumor

• The volume information of the tumor can be used to trace the variant state of the tumor in clinical applications