Breast Imaging
12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 – July 2, 2014. Proceedings
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16 Result(s)
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Takeshi Hara
Computer Science
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Chapter and Conference Paper
Automated Recognition of Erector Spinae Muscles and Their Skeletal Attachment Region via Deep Learning in Torso CT Images
Erector spinae muscle (ESM) is an important muscle in the torso region. Changes of sizes, shapes and densities in the cross section of the spinal column muscles have been found in chronic low back pain, degene...
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Chapter and Conference Paper
Three-Dimensional CT Image Segmentation by Combining 2D Fully Convolutional Network with 3D Majority Voting
We propose a novel approach for automatic segmentation of anatomical structures on 3D CT images by voting from a fully convolutional network (FCN), which accomplishes an end-to-end, voxel-wise multiple-class c...
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Book and Conference Proceedings
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Chapter and Conference Paper
Differentiation of Malignant and Benign Masses on Mammograms Using Radial Local Ternary Pattern
Texture information of breast masses may be useful in differentiating malignant from benign masses on digital mammograms. Our previous mass classification scheme relied on shape and margin features based on ma...
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Chapter and Conference Paper
Automatic Measurement of Vertical Cup-to-Disc Ratio on Retinal Fundus Images
Glaucoma is a leading cause of permanent blindness. Retinal fundus image examination is useful for early detection of glaucoma. In order to evaluate the presence of glaucoma, the ophthalmologist may determine ...
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Chapter and Conference Paper
State-of-the-Art of Computer-Aided Detection/Diagnosis (CAD)
This paper summarizes the presentations given in the special ICMB2010 session on state-of-the-art of computer-aided detection/diagnosis (CAD). The topics are concerned with the latest development of technologi...
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Chapter and Conference Paper
Classifying Breast Masses in Volumetric Whole Breast Ultrasound Data: A 2.5-Dimensional Approach
The aim of this paper is to investigate a 2.5-dimensional approach in classifying masses as benign or malignant in volumetric anisotropic voxel whole breast ultrasound data. In this paper, the term 2.5-dimensi...
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Chapter and Conference Paper
Development of Whole Breast Ultrasound Viewer and Automated Mass Detection System
Ultrasonography is one of the most important methods for breast cancer diagnosis in Japan. In general, the ultrasonography using conventional handheld probe is operator-dependent, therefore, the quality of ima...
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Chapter and Conference Paper
CAD on Brain, Fundus, and Breast Images
Three computer-aided detection (CAD) projects are hosted at the Gifu University, Japan as part of the “Knowledge Cluster Initiative” of the Japanese Government. These projects are regarding the development of ...
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Chapter and Conference Paper
Classification of Benign and Malignant Masses in Ultrasound Breast Image Based on Geometric and Echo Features
The aim of this paper is to study the use of geometric and echo features in classifying masses in ultrasound images as benign or malignant. While mammography is very effective in detecting masses and other les...
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Chapter and Conference Paper
Computerized Classification of Mammary Gland Patterns in Whole Breast Ultrasound Images
Several whole breast ultrasound (US) scanners have recently been developed for breast cancer screening. In ultrasonographic screening techniques that utilize scanners, assessment of the mammary gland pattern i...
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Chapter and Conference Paper
CAD on Liver Using CT and MRI
The incidence of liver diseases is very high in Asian countries. This paper introduces our computer-aided diagnosis (CAD) system for diagnosing liver cancer and describes the fundamental technologies employed ...
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Chapter and Conference Paper
Classifying Masses as Benign or Malignant Based on Co-occurrence Matrix Textures: A Comparison Study of Different Gray Level Quantizations
In this paper, co-occurrence matrix based texture features are used to classify masses as benign or malignant. As (digitized) mammograms have high depth resolution (4096 gray levels in this study) and the size...
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Chapter and Conference Paper
Development of Breast Ultrasound CAD System for Screening
Mass screening of breast cancer utilizing mammography (MMG) has been widely carried out. However, MMG might not be able to depict small impalpable masses in dense breast tissue clearly. We have developed a com...
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Chapter and Conference Paper
Constructing a Probabilistic Model for Automated Liver Region Segmentation Using Non-contrast X-Ray Torso CT images
A probabilistic model was proposed in this research for fully-automated segmentation of liver region in non-contrast X-ray torso CT images. This probabilistic model was composed of two kinds of probability tha...
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Chapter and Conference Paper
Automated Detection Method for Architectural Distortion with Spiculation Based on Distribution Assessment of Mammary Gland on Mammogram
The clustered microcalcifications and mass are the important findings in interpreting breast cancer, architectural distortion on mammograms as well. We have developed the detection algorithm for distorted area...
