Automatic bone detection and soft tissue aware ultrasound–CT registration for computer-aided orthopedic surgery

Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir

doi:10.1007/s11548-015-1208-z

Cited by 38 publications

(13 citation statements)

References 19 publications

(28 reference statements)

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“…The students were given written exams during the course that they had to complete before and after the course. They also had to complete an objective structured clinical examination (OSCE) and a questionnaire for their assessment after finishing the course [ 19 ]. Ultrasound bone identification and worldwide CT registrations have both been automated completely by our techniques.…”

Section: Related Workmentioning

confidence: 99%

Construction of a Computer-Aided Analysis System for Orthopedic Diseases Based on High-Frequency Ultrasound Images

Xiu

Rong

Zhang

2022

Computational and Mathematical Methods in Medicine

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The area of medical diagnosis has been transformed by computer-aided diagnosis (CAD). With the advancement of technology and the widespread availability of medical data, CAD has gotten a lot of attention, and numerous methods for predicting different pathological diseases have been created. Ultrasound (US) is the safest clinical imaging method; therefore, it is widely utilized in medical and healthcare settings with computer-aided systems. However, owing to patient movement and equipment constraints, certain artefacts make identification of these US pictures challenging. To enhance the quality of pictures for classification and segmentation, certain preprocessing techniques are required. Hence, we proposed a three-stage image segmentation method using U-Net and Iterative Random Forest Classifier (IRFC) to detect orthopedic diseases in ultrasound images efficiently. Initially, the input dataset is preprocessed using Enhanced Wiener Filter for image denoising and image enhancement. Then, the proposed segmentation method is applied. Feature extraction is performed by transform-based analysis. Finally, obtained features are reduced to optimal subset using Principal Component Analysis (PCA). The classification is done using the proposed Iterative Random Forest Classifier. The proposed method is compared with the conventional performance measures like accuracy, specificity, sensitivity, and dice score. The proposed method is proved to be efficient for detecting orthopedic diseases in ultrasound images than the conventional methods.

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Section: Related Workmentioning

confidence: 99%

Construction of a Computer-Aided Analysis System for Orthopedic Diseases Based on High-Frequency Ultrasound Images

Xiu

Rong

Zhang

2022

Computational and Mathematical Methods in Medicine

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“…Other element of the CAOS systems deals with incorporating surgeons and other clinical specialists and their insights from the clinical point of the view. As surgeons have special needs for specific surgical operations, technical specialists need to optimize the CAOS solutions for specific applications [259,260,261,262].…”

Section: Discussion and Future Perspectivesmentioning

confidence: 99%

Recent Trends, Technical Concepts and Components of Computer-Assisted Orthopedic Surgery Systems: A Comprehensive Review

Kubíček

Tomanec

Černý

et al. 2019

Sensors

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Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.

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“…Roche used the magnetic resonance intensity and grayscale information in MRI images to predict the grayscale of ultrasound images, but omitted some of the noisy situations such as signal attenuation and spotting [ 16 ]. Similarly, Wein used a physical model of ultrasound image production to convert CT images into ultrasound images in order to realize the registration of CT–ultrasound images [ 17 ].…”

Section: Cross-modal Conversion and Interpolative Algorithmsmentioning

confidence: 99%

A Review on Medical Image Registration as an Optimization Problem

Song

Han

Zhao

et al. 2017

CMIR

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Objective: In the course of clinical treatment, several medical media are required by a phy-sician in order to provide accurate and complete information about a patient. Medical image registra-tion techniques can provide a richer diagnosis and treatment information to doctors and to provide a comprehensive reference source for the researchers involved in image registration as an optimization problem.Methods: The essence of image registration is associating two or more different images spatial asso-ciation, and getting the translation of their spatial relationship. For medical image registration, its pro-cess is not absolute. Its core purpose is finding the conversion relationship between different images.Result: The major step of image registration includes the change of geometrical dimensions, and change of the image of the combination, image similarity measure, iterative optimization and interpo-lation process.Conclusion: The contribution of this review is sort of related image registration research methods, can provide a brief reference for researchers about image registration.

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Automatic bone detection and soft tissue aware ultrasound–CT registration for computer-aided orthopedic surgery

Abstract: Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

Cited by 38 publications

References 19 publications

Construction of a Computer-Aided Analysis System for Orthopedic Diseases Based on High-Frequency Ultrasound Images

Construction of a Computer-Aided Analysis System for Orthopedic Diseases Based on High-Frequency Ultrasound Images

Recent Trends, Technical Concepts and Components of Computer-Assisted Orthopedic Surgery Systems: A Comprehensive Review

A Review on Medical Image Registration as an Optimization Problem

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