Sato, Kimihiko Kanai, Takayuki Lee, Sung Hyun Miyasaka, Yuya Chai, Hongbo Souda, Hikaru Iwai, Takeo Sato, Ryuji Goto, Naoki Kawamura, Tsukasa
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Published in
Radiological physics and technology
This study aimed to develop a new method to quantitatively analyze body shape changes in patients during radiotherapy without additional radiation exposure using an optical surface tracking system. This method's accuracy was evaluated using a cubic phantom with a known shift. Surface images of three-dimensionally printed phantoms, which simulated t...
Ecker, Stefan Zimmermann, Lukas Heilemann, Gerd Niatsetski, Yury Schmid, Maximilian Sturdza, Alina Emiliana Knoth, Johannes Kirisits, Christian Nesvacil, Nicole
Published in
Zeitschrift fur medizinische Physik
In image-guided adaptive brachytherapy (IGABT) a quantitative evaluation of the dosimetric changes between fractions due to anatomical variations, can be implemented via rigid registration of images from subsequent fractions based on the applicator as a reference structure. With available treatment planning systems (TPS), this is a manual and time-...
Chen, Junyu Frey, Eric C He, Yufan Segars, William P Li, Ye Du, Yong
Published in
Medical image analysis
In the last decade, convolutional neural networks (ConvNets) have been a major focus of research in medical image analysis. However, the performances of ConvNets may be limited by a lack of explicit consideration of the long-range spatial relationships in an image. Recently, Vision Transformer architectures have been proposed to address the shortco...
Ying, Jia Cattell, Renee Zhao, Tianyun Lei, Lan Jiang, Zhao Hussain, Shahid M Gao, Yi Chow, H-H Sherry Stopeck, Alison T Thompson, Patricia A
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Published in
Visual computing for industry, biomedicine, and art
Presence of higher breast density (BD) and persistence over time are risk factors for breast cancer. A quantitatively accurate and highly reproducible BD measure that relies on precise and reproducible whole-breast segmentation is desirable. In this study, we aimed to develop a highly reproducible and accurate whole-breast segmentation algorithm fo...
Bierbrier, Joshua Gueziri, Houssem-Eddine Collins, D Louis
Published in
Medical image analysis
Given that image registration is a fundamental and ubiquitous task in both clinical and research domains of the medical field, errors in registration can have serious consequences. Since such errors can mislead clinicians during image-guided therapies or bias the results of a downstream analysis, methods to estimate registration error are becoming ...
Retif, Paul Djibo Sidikou, Abdourahamane Mathis, Christian Letellier, Romain Verrecchia-Ramos, Emilie Dupres, Rémi Michel, Xavier
Published in
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Cranial stereotactic radiotherapy (SRT) requires highly accurate lesion delineation. However, MRI can have significant inherent geometric distortions. We investigated how well the Elements Cranial Distortion Correction algorithm of Brainlab (Munich, Germany) corrects the distortions in MR image-sets of a phantom and patients. A non-distorted refere...
Riegel, Adam C Cooney, Ann To, Samantha Guest, Deborah Lee, Brisca Lim, May Potters, Louis
Published in
Brachytherapy
Combining external beam radiation therapy (EBRT) and prostate seed implant (PSI) is efficacious in treating intermediate- and high-risk prostate cancer at the cost of increased genitourinary toxicity. Accurate combined dosimetry remains elusive due to lack of registration between treatment plans and different biological effect. The current work pro...
Fourcade, Constance Ferrer, Ludovic Moreau, Noémie Santini, Gianmarco Brennan, Aislinn Rousseau, Caroline Lacombe, Marie Fleury, Vincent Colombié, Mathilde Jézéquel, Pascal
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Published in
Physics in Medicine & Biology
Objective. This paper proposes a novel approach for the longitudinal registration of PET imaging acquired for the monitoring of patients with metastatic breast cancer. Unlike with other image analysis tasks, the use of deep learning (DL) has not significantly improved the performance of image registration. With this work, we propose a new registrat...
Liu, Peilu de Hoop, Hein Schwab, Hans-Martin Lopata, Richard G P
Published in
Ultrasonics
Ultrasound (US) imaging is used to assess cardiac disease by assessing the geometry and function of the heart utilizing its high spatial and temporal resolution. However, because of physical constraints, drawbacks of US include limited field-of-view, refraction, resolution and contrast anisotropy. These issues cannot be resolved when using a single...
Wang, Di Pan, Yue Durumeric, Oguz C Reinhardt, Joseph M Hoffman, Eric A Schroeder, Joyce D Christensen, Gary E
Published in
Medical image analysis
This paper presents the Population Learning followed by One Shot Learning (PLOSL) pulmonary image registration method. PLOSL is a fast unsupervised learning-based framework for 3D-CT pulmonary image registration algorithm based on combining population learning (PL) and one-shot learning (OSL). The PLOSL image registration has the advantages of the ...
