Deep-learning model enables rapid lymphoma detection in PET/CT images
A convolutional neural network model that detects lymphoma lesions in PET/CT scans could enable faster diagnosis and monitoring of treatment efficacy
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Laura Patricia Kaplan is a PhD student contributor to Physics World. She is part of a research group working on computational radiation therapy physics at the Department of Oncology and the Danish Center for Particle Therapy in Aarhus, Denmark. Her research focuses on quantitative analysis and comparison of radiation treatment plans, both for aiding in the treatment planning process and making treatments more personalized.
Outside of her office, Laura can usually be found at the local music school, where she sings in an ambitious women’s choir, or on her couch with a good book.
A convolutional neural network model that detects lymphoma lesions in PET/CT scans could enable faster diagnosis and monitoring of treatment efficacy
Exploiting the increased sound wave generation during FLASH radiotherapy could enable real-time monitoring of both the deposited dose and the patient’s anatomy
Patients with oligometastatic prostate cancer treated with stereotactic ablative radiotherapy had longer progression-free survival than observation-only controls
PhD student Laura Patricia Kaplan shares her thoughts on working from home
Computational analysis of MRI scans from glioblastoma patients may help predict survival and response to treatments
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