3-D Elastic Matching Technique for Temporal Subtraction Employing Thorax MDCT Images

Itai, Y; Kim, Hyoungseop; Ishikawa, Seiji; Katsuragawa, Shigehiko; Ishida, Takayuki; Kawashita, Ikuo; Awai, Kazuo; Li, Qiang; Doi, Kunio

doi:10.1007/978-3-540-36841-0_581

Cited by 2 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, the bottom row of each table shows average of evaluation values of all cases. Our proposed method achieved best performance compare with previous methods [8], as shown in Fig. 5.…”

Section: B Resultsmentioning

confidence: 77%

“…here matrix M needs to be a positive definite in order to get solution (8), which is guaranteed when corresponding point before deformation c k satisfies the condition of Schoenberg-Whitney. Thus we arrange c k , which is a coordinate before deformation, as a basic point and set a k , which is a coordinate after deformation, corresponding with each basic point.…”

Section: B Non-rigid Warping Methodsmentioning

confidence: 99%

“…Thus we arrange c k , which is a coordinate before deformation, as a basic point and set a k , which is a coordinate after deformation, corresponding with each basic point. The amount of deformation in q is obtained uniquely by setting parameter P in (6) and (8).…”

Section: B Non-rigid Warping Methodsmentioning

confidence: 99%

“…1. We have already proposed a voxel-based nonrigid image registration algorithms for temporal subtraction image, which is obtained by subtraction of a previous image from a current one on Multiple Detector Computed Tomography (MDCT) of the same object [8]- [11]. Using our algorithms, the temporal changes of the lung region can be emphasized.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A 3-D Non-Rigid Warping Method Based on Free Formed Deformation for Temporal Subtraction on Thoracic MDCT Images

Yoshino¹,

Tokisa²,

Kim³

et al. 2016

JOIG

Self Cite

View full text Add to dashboard Cite

Recently, the development of the Computer Aided Diagnoses (CAD) systems has been rapidly remarked. As one of the CAD systems, temporal subtraction technique can emphasize the temporal changes of interested regions by subtracting a previous image from a current image. However, subtraction artifacts are still remained due to misregistration, which caused by the variation of pose and inhalation differences when a patient accepts CT inspection at different times. Therefore, high accurate registration technique between a previous image and a current image is necessary. The purpose of this paper is to propose a nonrigid warping algorithm in local image matching based on the feature-driven Free Formed Deformation (FFD). The proposal was performed on thoracic MDCT images and the satisfactory results were obtained.

show abstract

Section: B Resultsmentioning

confidence: 77%

Section: B Non-rigid Warping Methodsmentioning

confidence: 99%

Section: B Non-rigid Warping Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A 3-D Non-Rigid Warping Method Based on Free Formed Deformation for Temporal Subtraction on Thoracic MDCT Images

Yoshino¹,

Tokisa²,

Kim³

et al. 2016

JOIG

Self Cite

View full text Add to dashboard Cite

show abstract

“…Fig.1 shows an example of temporal subtraction image which is subtracted from the two images using the subtraction technique. However, the subtraction artifacts due to the mis-registration still exist on the temporal subtraction images [11][12][13][14]. It cause t he false positives of lung nodules when the detection on temporal subtraction images.…”

Section: Introductionmentioning

confidence: 99%

Detection of Lung Nodule on Temporal Subtraction Images Based on Artificial Neural Network

Tokisa¹,

Miyake²,

Maeda³

et al. 2012

International Journal of Fuzzy Logic and Intelligent Systems

Self Cite

View full text Add to dashboard Cite

The temporal subtraction technique as one of computer aided diagnosis has been introduced in medical fields to enhance the interval changes such as formation of new lesions and changes in existing abnormalities on deference image. With the temporal subtraction technique radiologists can easily detect lung nodules on visual screening. Until now, two-dimensional temporal subtraction imaging technique has been introduced for the clinical test. We have developed new temporal subtraction method to remove the subtraction artifacts which is caused by mis-registration on temporal subtraction images of lungs on MDCT images. In this paper, we propose a new computer aided diagnosis scheme for automatic enhancing the lung nodules from the temporal subtraction of thoracic MDCT images. At first, the candidates regions included nodules are detected by the multiple threshold technique in terms of the pixel value on the temporal subtraction images. Then, a rule-base method and artificial neural networks is utilized to remove the false positives of nodule candidates which is obtained temporal subtraction images. We have applied our detection of lung nodules to 30 thoracic MDCT image sets including lung nodules. With the detection method, satisfactory experimental results are obtained. Some experimental results are shown with discussion.

show abstract

3-D Elastic Matching Technique for Temporal Subtraction Employing Thorax MDCT Images

Cited by 2 publications

References 8 publications

A 3-D Non-Rigid Warping Method Based on Free Formed Deformation for Temporal Subtraction on Thoracic MDCT Images

A 3-D Non-Rigid Warping Method Based on Free Formed Deformation for Temporal Subtraction on Thoracic MDCT Images

Detection of Lung Nodule on Temporal Subtraction Images Based on Artificial Neural Network

Contact Info

Product

Resources

About