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10 Feb 2025 • Journal Article • Optics Express
Point spread function modeling and engineering in black-box lens systems
AbstractPoint spread function (PSF) engineering in an imaging system involves the introduction of additional optical components to efficiently encode object information. It typically relies on a well-established mapping relation between object space, PSF engineering plane, and image plane. However, this reliance can limit its application in imaging systems with unknown (“black
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2 Feb 2025 • Preprint • arXiv
Agent-Based Uncertainty Awareness Improves Automated Radiology Report Labeling with an Open-Source Large Language Model
AbstractReliable extraction of structured data from radiology reports using Large Language Models (LLMs) remains challenging, especially for complex, non-English texts like Hebrew. This study introduces an agent-based uncertainty-aware approach to improve the trustworthiness of LLM predictions in medical applications. We analyzed 9,683 Hebrew radiology reports from Crohn's
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Feb 2025 • Journal Article • Optics & Laser Technology
Advancing automated digital pathology by rapid spectral imaging and AI for nuclear segmentation
AbstractCancer is one of the leading causes of death worldwide and stained tissues’ biopsy analysis remains the standard method for pathology diagnostics. Major optical developments have improved pathological diagnostics lately. High quality microscopic optical scanners now allow whole-slide imaging of tissue sections and with the accessibility of datasets, digital imaging
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Feb 2025 • Journal Article • Computer Methods and Programs in Biomedicine
CIMIL-CRC: A clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H&E stained images
AbstractBackground and objective: Treatment approaches for colorectal cancer (CRC) are highly dependent on the molecular subtype, as immunotherapy has shown efficacy in cases with microsatellite instability (MSI) but is ineffective for the microsatellite stable (MSS) subtype. There is promising potential in utilizing deep neural networks (DNNs) to automate the differentiation
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31 Jan 2025 • Journal Article • Advanced Healthcare Materials
Bioprinting Perfusable and Vascularized Skeletal Muscle Flaps for the Treatment of Volumetric Muscle Loss
AbstractVolumetric muscle loss (VML) refers to muscle tissue loss exceeding 20% within a functional area due to trauma or surgery, often leading to physical disabilities. VML treatment relies on the transplantation of autologous flaps harvested from a healthy-donor site while minimizing the probability of immune rejection. However, this approach often leads to donor-site
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31 Jan 2025 • Journal Article • Journal of Controlled Release
Mastering the complexities of cancer nanomedicine with text mining, AI and automation
AbstractIn this contribution to the Orations - New Horizons of the Journal of Controlled Release, I present a personal perspective on the complexities of cancer nanomedicine and the approaches to master them. This oration draws mainly from my lab's journey to explore three transformative approaches to master complexities in the field: (1) leveraging text mining to construct
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28 Jan 2025 • Journal Article • Biofabrication
Rational design of 3D-printed scaffolds for breast tissue engineering using structural analysis
AbstractBest cosmetic outcomes of breast reconstruction using tissue engineering techniques rely on the scaffold architecture and material, which are currently both to be determined. This study suggests an approach for a rational design of breast-shaped scaffold architecture, in which structural analysis is implemented to predict its stiffness and adjust it to that of the native
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23 Jan 2025 • Journal Article • Medical & Biological Engineering & Computing
Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment
AbstractPositron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection of metastatic tumors and response to therapy assessment due to its high sensitivity compared to anatomical imaging modalities. The balance between image quality and radiation exposure is critical, as reducing the administered dose results in a lower signal-to-noise ratio
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22 Jan 2025 • Journal Article • Physiological Measurement
Deep learning generalization for diabetic retinopathy staging from fundus images
AbstractObjective. Diabetic retinopathy (DR) is a serious diabetes complication that can lead to vision loss, making timely identification crucial. Existing data-driven algorithms for DR staging from digital fundus images (DFIs) often struggle with generalization due to distribution shifts between training and target domains. Approach. To address this, DRStageNet, a deep learning
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19 Jan 2025 • Journal Article • Acta Ophthalmologica
Automated analysis of retinal vascular features, age, sex and disc size in a large cohort of primary open angle glaucoma patients
AbstractAims/Purpose: Deriving vascular features of retinal images is a proposed noninvasive method to assess vascular health. Although several studies have linked cardiovascular risk to retinal image features, they often rely on limited datasets or have used deep learning approaches with limited explainability. This research introduces an end-to-end method for analyzing the
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