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type:Journal Article, Image registration is an important problem and a fundamental task in com-puter vision and image processing field. Recently, many image registration techniques are introduced such as PET with CT image and abnormalities can be easily detected by using image information. One of the multi modal images, CT and MR imaging of the head for diagnosis and surgical planning indicates that physicians and surgeons gain impor- tant information from these modalities. In radiotherapy planning, manual registration techniques are performed on MR and CT images of the brain. In general, physicians segment the volumes of interest (VOIs) from each set of slices on the MR and CT im- ages manually. However, manual registration of the object may require several hours for analysis based on anatomical knowledge. In this paper, we describes a new method for automatic registration of head images which is obtained CT and MRI by using an optimal retrieval on neighbor VOIs in several extracted data and maximization of mutual information. In the experimental results, we can reduce the computational times. The primary objective of this study is to increase accuracy of the registration and reduce the computational processing time.

type:Journal Article, Recently, the disease arteriosclerosis has rapidly increased, and in particular the type that originates in the peripheral arteries of the hands and feet and is called arteriosclerosis obliterans (ASO). ASO is one of the typical diseases that cause chronic ischemia of the limbs and lead to obstruction of the blood flow. In diagnosing ASO, lower contrast enhanced computed tomography (CT) is useful for observing the arteries. However, it is a huge task for radiologists to separate accurately only the arteries which are involved in the disease, using the manual or semiautomatic proprietary software which is supplied for lower computed tomographic angiography (CTA). We have developed a new technique for the detection of arteries from CTA images by the use of a morphological operation. In this technique an N-Quoit filter, which is a useful filter for the detection of lung nodules, is applied to identify the arteries in CTA images. Some experimental results have shown good performance in the segmentation of arteries., This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008

type:Conference Paper, Image registration is an important and a fundamental task in computer vision and image processing field. For example, to make a surgical plan for head operation, the surgeons should gain more detailed information from CT angiography (CTA) and MR angiography (MRA) images. And the abnormalities can be easily detected from the fusion image which is obtained from two different modalities. One of the multiple modal image registration methods is matching the CTA and MRA, by which the image of head vascular could be enhanced. In general, the procedure for fusion is completed manually. It is time-consuming and subjective. Particularly the anatomical knowledge is required as well. Therefore, the development of automatic registration methods is expected in medical fields. In this paper, we propose a method for high accurate registration, which concentrates the structure of head vascular. We use 2-D projection images and restrict volume of interests to improve the processing affection. In experiments, we performed our proposed method for registration on five sets of CTA and MRA images and a better result from our previous method is obtained., SCIS&ISIS 2014 : Joint 7th International Conference on Soft Computing and Intelligent Systems and 15th International Symposium on Advanced Intelligent, December 3-6, 2014, Kitakyushu, Japan, source:DOI: 10.1109/SCIS-ISIS.2014.7044848

近年、MDCT装置の普及、機能向上に伴い、より高精細な CT画像が日常的に用いられるようになった。一方で一度の撮影で得られる画像枚数は膨大な量となり、読影にあたる医師への負担は増加している。そのため計算機を用いた多臓器・多疾病に対する診断支援(CAD)システムの開発への要望が高まっている。多臓器・多疾病に対するCADシステムの構築にあたり、3 次元CT像上の病変の特徴は臓器ごとに異なっている。そのため病変の検出を行うには、あらかじめ各臓器を正確に抽出する必要がある。特に心臓領域の抽出分野においては造影画像を対象とした研究が報告されているが、非造影画像を対象とした手法は抽出手法に関する報告は少ないのが現状である。本稿では、胸部非造影CT画像を用いた複数臓器の自動抽出手法の開発を行う。手法としては、閾値処理と3次元リージョングローイング法により肺臓領域の抽出を行い、濃度値に依存した抽出が困難な心臓領域に対してはテンプレート・マッチング法を用いた抽出を試みた。提案手法を6症例の実CT画像に適用し、肺臓領域抽出において一致度96%、心臓領域抽出において一致度75%を得た。Recently, various imaging equipment have been introduced into medical imaging fields. Especially, MDCT is one of the most useful diagnosis systems because it provides a high resolution image to medical doctors. Accordingly, many related image processing techniques are proposed into medical fields for extraction of abnormal area. In the medical image processing field, segmentation is one of the most important problems for analyzing abnormalities. Many related segmentation techniques have been developed for automatic extraction of ROI. In this paper, we propose a new technique for automatic extraction of the multi organs on the breast MDCT images employing the 3D region growing and template matching technique. We apply the proposed technique for extraction of lung and heart region to six CT Cases and satisfactory results are achieved.

第23回バイオメディカル.ファジイ･システム学会年次大会, 2010年10月9日(土).10日(日)北九州

近年,様々な画像解析技術が医療現場に導入されるようになった。特にHRCTは,有用性の高い診断システムの一つとして高い評価を得ている。腹部CT画像を用いた診断においても,高分解能を有するCT画像から,術前に患者の血管領域の構造を把握するなど,様々な用途で利用されている。これらの画像解析を行うには,対象領域のセグメンテーション技術が必要であり,領域抽出に関する研究が盛んに行われている。一方、2つの異なる時期に作成される画像からの差分演算を行い,変化部位を強調するための経時差分技法が用いられている。経時差分技法において最も重要視されているのは,過去画像と現在画像の正確な位置合わせを行うための画像変形(ワーピング)処理である。ワーピングが正確に行われていなければ,差分画像上において位置ずれによるアーチファクトが発生し,画質が低下するという問題が生じる。本稿では,従来用いられている2次元経時差分技法を3次元に拡張し,腹部MDCT画像に適用することにより,血管領域の抽出を試みる。提案する手法を実腹部CT画像4症例に適用した結果について述べる。; In recent years, various imaging techniques have been introduced into medical fields for extraction of internal organ. Especially, HRCT is one of the useful diagnosis systems because it provides high resolution images. In the field of abdominal CT images, it is very important to understand blood vessel structures of a patient before operation. Furthermore, in the medical imaging field, segmentation is one of the most important problems. On the other hand, temporal subtraction method attempt to remove normal structures in the CT images, so that abnormalities can be observed more clearly to the medical doctor. With the subtraction technique, image warping is very important. If the performance of warping is no good, normal structures will appear as the artifacts on the subtraction image, and the image quality can be degraded. In this paper, we propose a 3-dimentional temporal subtraction method for abdominal CT images in order to detect the blood vessel region. The proposed technique is applied to four abdominal CT images and satisfactory results are achieved.