Bruna Cotrufo

Towards reliable no-reference image quality assessment in photoacoustic imaging

Bruna Cotrufo, Andrea Ferraris, Silvia Seoni, Massimo Salvi et autres

Assessing image quality in photoacoustic imaging remains an open challenge, particularly due to the lack of reference images in in vivo settings. While simulated data can provide ground truth for objective evaluation, traditional metrics often fail to capture artefacts and degradations that …

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Photoacoustic characterization of an ultrasound-transparent high-density surface EMG array

Alberto Botter, Silvia Seoni, Matteo Garrione, Elena Cesti et autres

We present a photoacoustic characterization of a high-density, ultrasound-transparent surface EMG electrode array designed for multimodal biomedical imaging. While such electrodes have been shown to preserve ultrasound image quality, their interaction with photoacoustic signals has remained unexplored. Using a tissue-mimicking phantom with …

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Hierarchical materials based on polydimethylsiloxane as tissue-like phantoms for AI-enhanced photoacoustic imaging

Lucia Cavigli, Fulvio Ratto, Sonia Centi, Francesca Rossi et autres

Hierarchical materials as tissue-like phantoms for photoacoustic imaging

Lucia Cavigli, Sonia Centi, Fulvio Ratto, Francesca Rossi et autres

We introduce a hierarchical manufacturing method for creating anatomical phantoms using water-in-elastomer micro-emulsions. This approach addresses the cost, ethical, and technical limitations of animal models, providing a reliable alternative for multimodal imaging and artificial intelligence development, particularly in photoacoustic imaging.

Hierarchical materials based on polydimethylsiloxane as tissue-like phantoms for photoacoustic imaging and diffusive optics

Fulvio Ratto, Alessandro Bossi, Laura Di Sieno, Sonia Centi et autres

The rise of multimodal imaging and treatments, particularly with optical tools, promises to make a disruptive impact on clinical problems such as cancer and infectious conditions, especially in critical sites like the lungs. However, ethical concerns and the high costs of using …

A pilot study on the use of high‐frequency photoacoustic imaging for quantitative human skin vasculature analysis

Bruna Cotrufo, Alberto Vallan, Silvia Seoni, Giacinto Luigi Cerone et autres

The assessment of skin health often relies on detailed visualization of skin architecture and its underlying vascular structures. A non-invasive technique which allows vasculature imaging is photoacoustic imaging (PAI), a hybrid modality that combines advantages from both optical and ultrasound imaging. This …

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Exploring uncertainty quantification for photoacoustic image reconstruction and quantitative oxygenation mapping

Silvia Seoni, Roberto Maria Scardigno, Bruna Cotrufo, Massimo Salvi et autres

Deep learning (DL) has recently been employed to enhance photoacoustic (PA) image reconstruction and quantify blood oxygenation. A significant challenge with artificial intelligence (AI) methods is the inability to quantify errors for validating predictions when the ground truth is unknown. Hence, evaluating …

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Hierarchical materials as tissue-like phantoms for photoacoustic imaging

Lucia Cavigli, Sonia Centi, Fulvio Ratto, Francesca Rossi et autres

We introduce a hierarchical manufacturing method for creating anatomical phantoms using water-in-elastomer micro-emulsions. This approach addresses the cost, ethical, and technical limitations of animal models, providing a reliable alternative for multimodal imaging and artificial intelligence development, particularly in photoacoustic imaging.

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Plasmonic Particles for Optical Phantoms of Blood Tissue

Fulvio Ratto, Sonia Centi, Francesca Rossi, Giada Magni et autres

The biomedical engineering field faces significant challenges in transitioning innovations from proof-of-concept to practical applications. Animal models often contribute to these hurdles due to high costs, ethical concerns, as well as technical limitations. The development of reliable, low-cost, and multipurpose phantoms to …

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cyto‐Knet : An instance segmentation approach for multiple myeloma plasma cells using conditional kernels

Massimo Salvi, Nicola Michielli, Kristen M. Meiburger, Cristina Cattelino et autres

Abstract Multiple myeloma disrupts normal blood cell production, requiring early detection due to the increased risk of bone metastases. Although various artificial intelligence (AI) methods have been developed to assist pathologists, they often lack comprehensive metrics to measure both detection and segmentation …

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