1. Articles from Kyle Newman

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    1. Quantitative Micro-Elastography Enables In Vivo Detection of Residual Cancer in the Surgical Cavity during Breast-Conserving Surgery

      Quantitative Micro-Elastography Enables In Vivo Detection of Residual Cancer in the Surgical Cavity during Breast-Conserving Surgery

      Breast-conserving surgery (BCS) is commonly used for the treatment of early-stage breast cancer. Following BCS, approximately 20% to 30% of patients require reexcision because postoperative histopathology identifies cancer in the surgical margins of the excised specimen. Quantitative micro-elastography (QME) is an imaging technique that maps microscale tissue stiffness and has demonstrated a high diagnostic accuracy (96%) in detecting cancer in specimens excised during surgery. However, current QME methods, in common with most proposed intraoperative solutions, cannot image cancer directly in the patient, making their translation to clinical use challenging. In this proof-of-concept study, we aimed to determine whether a handheld ...

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    2. Multi-class classification of breast tissue using optical coherence tomography and attenuation imaging combined via deep learning

      Multi-class classification of breast tissue using optical coherence tomography and attenuation imaging combined via deep learning

      We demonstrate a convolutional neural network (CNN) for multi-class breast tissue classification as adipose tissue, benign dense tissue, or malignant tissue, using multi-channel optical coherence tomography (OCT) and attenuation images, and a novel Matthews correlation coefficient (MCC)-based loss function that correlates more strongly with performance metrics than the commonly used cross-entropy loss. We hypothesized that using multi-channel images would increase tumor detection performance compared to using OCT alone. 5,804 images from 29 patients were used to fine-tune a pre-trained ResNet-18 network. Adding attenuation images to OCT images yields statistically significant improvements in several performance metrics, including benign dense ...

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    1-2 of 2
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  2. Topics in the News

    1. (2 articles) University of Western Australia
    2. (1 articles) Thorlabs
    3. (1 articles) OncoRes Medical
    4. (1 articles) Academic Medical Center at the University of Amsterdam
    5. (1 articles) University College London
    6. (1 articles) University of Cologne
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    Multi-class classification of breast tissue using optical coherence tomography and attenuation imaging combined via deep learning Quantitative Micro-Elastography Enables In Vivo Detection of Residual Cancer in the Surgical Cavity during Breast-Conserving Surgery A Deep Learning Framework for the Detection and Quantification of Reticular Pseudodrusen and Drusen on Optical Coherence Tomography Quantitative assessment of textural features in the early detection of diabetic retinopathy with optical coherence tomography angiography Line-field confocal optical coherence tomography of fibroepithelioma of Pinkus Assessment of demineralized tooth lesions using optical coherence tomography and other state-of-the-art technologies: a review Optic disc and retinal vessel densities assessment by optical coherence tomography angiography in patients with keratoconus Optical coherence tomography angiography in Bietti crystalline dystrophy Choroidal vascularity profile in diabetic eyes using wide field optical coherence tomography Diagnostic accuracy of OCTA and OCT for myopic choroidal neovascularisation: a systematic review and meta-analysis All Eyes on Pcs - Analysis of the Retinal Microvasculature in Patients With Post-COVID-19 Syndrome Training Health Care Professional in Detecting BCC on OCT Using E-learning and CUSUM-analysis