1. 10 Feb 2025 Journal Article Optics Express

    Point spread function modeling and engineering in black-box lens systems

    Abstract

    Point 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. 2 Feb 2025 Preprint arXiv

    Agent-Based Uncertainty Awareness Improves Automated Radiology Report Labeling with an Open-Source Large Language Model

    Hadas Ben Atya, Naama Gavrielov, Zvi Badash, Gili Focht, Ruth Cytter-Kuint, Talar Hagopian, Dan Turner, Moti Freiman
    Abstract

    Reliable 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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  3. Feb 2025 Journal Article Optics & Laser Technology

    Advancing automated digital pathology by rapid spectral imaging and AI for nuclear segmentation

    Adam Soker, Eugene Brozgol, Iris Barshack, Yuval Garini
    Abstract

    Cancer 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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  4. 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

    Abstract

    Background 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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  5. 31 Jan 2025 Journal Article Advanced Healthcare Materials

    Bioprinting Perfusable and Vascularized Skeletal Muscle Flaps for the Treatment of Volumetric Muscle Loss

    Abstract

    Volumetric 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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  6. 31 Jan 2025 Journal Article Journal of Controlled Release

    Mastering the complexities of cancer nanomedicine with text mining, AI and automation

    Abstract

    In 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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  7. 28 Jan 2025 Journal Article Biofabrication

    Rational design of 3D-printed scaffolds for breast tissue engineering using structural analysis

    Abstract

    Best 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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  8. 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

    Abstract

    Positron 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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  9. 22 Jan 2025 Journal Article Physiological Measurement

    Deep learning generalization for diabetic retinopathy staging from fundus images

    Yevgeniy Men, Jonathan Fhima, Leo Anthony Celi, Lucas Zago Ribeiro, Luis Filipe Nakayama, Joachim Behar
    Abstract

    Objective. 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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  10. 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

    Jan Van Eijgen, Jonathan Fhima, Anat Reiner Benaim, Lennert Beeckmans, Or Abramovich, Ingeborg Stalmans, Joachim Behar
    Abstract

    Aims/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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