A Framework for Image-Guided Breast Surgery

Carter, T. J.; Tanner, Christine; Crum, William R.; Beechey-Newman, N.; Hawkes, David J.

doi:10.1007/11812715_26

Cited by 23 publications

(22 citation statements)

References 7 publications

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“…Using the same biomechanical model, two different mammograms are correlated, helping radiologists to evaluate susceptible areas. Furthermore, a computer‐assisted diagnosis system can also be improved using multimodal features to classify the lesions or using the capabilities of the biomechanical model to track tumors in image‐guide procedures …”

Section: Evaluation Methods and Clinical Applicationsmentioning

confidence: 99%

“…Furthermore, a computer-assisted diagnosis system can also be improved using multimodal features to classify the lesions 23 or using the capabilities of the biomechanical model to track tumors in image-guide procedures. 87 However, so far, the application of these algorithms is not available in the clinical practice. Several works demonstrate that a multimodal combination leads to a more accurate diagnosis and treatment of the breast diseases from a medical point of view.…”

Section: Referencementioning

confidence: 99%

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A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

et al. 2017

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Breast magnetic resonance imaging (MRI) and x-ray mammography are two image modalities widely used for the early detection and diagnosis of breast diseases in women. The combination of these modalities leads to a more accurate diagnosis and treatment of breast diseases. The aim of this paper is to review the registration between breast MRI and x-ray mammographic images using patient-specific finite element-based biomechanical models. Specifically, a biomechanical model is obtained from the patient's MRI volume and is subsequently used to mimic the mammographic acquisition. Due to the different patient positioning and movement restrictions applied in each image modality, the finite element analysis provides a realistic physics-based approach to perform the breast deformation. In contrast with other reviews, we do not only expose the overall process of compression and registration but we also include main ideas, describe challenges, and provide an overview of the used software in each step of the process. Extracting an accurate description from the MR images and preserving the stability during the finite element analysis require an accurate knowledge about the algorithms used, as well as the software and underlying physics. The wide perspective offered makes the paper suitable not only for expert researchers but also for graduate students and clinicians. We also include several medical applications in the paper, with the aim to fill the gap between the engineering and clinical performance.

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Section: Evaluation Methods and Clinical Applicationsmentioning

confidence: 99%

Section: Referencementioning

confidence: 99%

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

et al. 2017

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“…There are described strategies to model breast deformations. However, each technique is usually designed for specialized applications: estimate pose transformation [5]- [10], model breast deformation [11] [12] [13] [14], predict the healing process of the breast after tumor removal [15] [16], among others. Vavourakis et al [16], proposed a 3D surgical simulator to predict a patient-specific outcome after BCS.…”

Section: Introductionmentioning

confidence: 99%

A Model to Predict Cosmetic Outcome after Breast Conservation Surgery

Tian¹

2018

OALib

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“…Previous work [1] has outlined a framework for image-guided breast surgery which uses a biomechanical model to link preoperative MR imaging with surgery. In this paper we develop the framework, focusing on presenting an improved biomechanical model of the deformation and on assessing the registration on a greater number of subjects.…”

Section: Introductionmentioning

confidence: 99%

MR Navigated Breast Surgery: Method and Initial Clinical Experience

Carter

Tanner

Beechey-Newman

et al. 2008

Lecture Notes in Computer Science

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3D dynamic contrast enhanced magnetic resonance (MR) images may help to reduce the high re-excision rate associated with breast conserving surgery. However these images are acquired prone, whilst surgery is performed supine which results in a large deformation that limits their usefulness. We describe here a registration technique based on a biomechanical model to account for soft tissue deformation between prone MR imaging and surgery. The accuracies of the individual registration steps are assessed off-line. We then report our first clinical experience with an image-guided surgery system which incorporates these algorithms. The system's accuracy is assessed against tracked ultrasound images, and is determined to be around 5mm for this case.

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A Framework for Image-Guided Breast Surgery

Cited by 23 publications

References 7 publications

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

A Model to Predict Cosmetic Outcome after Breast Conservation Surgery

MR Navigated Breast Surgery: Method and Initial Clinical Experience

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