Early Choriocapillaris Dysfunction in Fellow Eyes of Patients with Unilateral Neovascular Age-Related Macular Degeneration.

Purpose: To investigate early changes in AMD by evaluating and comparing choriocapillaris (CC) flow in fellow eyes of patients with unilateral neovascular age-related macular degeneration (nAMD) and in healthy controls using swept-source optical coherence tomography angiography (SS-OCTA).

Methods: Patients with unilateral nAMD and no/early/intermediate AMD (no/e/iAMD) in their fellow eye and normal controls who underwent SS-OCT and OCTA where included. CC perfusion was assessed on MATLAB as percentage of flow deficits (FD%) in the central 4.

Microvascular changes in eyes with non-proliferative diabetic retinopathy with or without macular microaneurysms: an OCT-angiography study.

Purpose: To evaluate different quantitative non-invasive retinal biomarkers of microvascular impairment and neurodegeneration in patients affected by mild and moderate non proliferative diabetic retinopathy (NPDR) with or without macular microaneurysms (MAs).

Methods: A cross-sectional case-control study. Ninety-seven eyes with NPDR, 49 with no central MAs and 48 with central MAs, underwent color fundus photography and optical coherence tomography (OCT)/OCT-angiography (OCT-A).

A gender-based analysis of retinal microvascular alterations in patients with diabetes mellitus using OCT angiography.

Purpose: To assess the difference in microvascular changes between males and females with diabetes mellitus (DM) without diabetic retinopathy (NoDR) and with mild-to-moderate non-proliferative diabetic retinopathy (NPDR) using Optical Coherence Tomography Angiography (OCT-A).

Design: Retrospective cross-sectional study.

Methods: 267 DM patients, 133 females (49.

Severity of Disorganization of Retinal Layers and Visual Function Impairment in Diabetic Retinopathy.

Purpose: To evaluate best-corrected visual acuity (BCVA), retina sensitivity (RS), and fixation impairment by microperimetry (MP) due to the presence and severity of disorganization of retinal inner and outer layers (DRIL/DROL) and ischemia in OCT/OCT angiography (OCTA) in diabetic retinopathy (DR).

Design: Retrospective case-control study.

Subjects: Seventy-six eyes (65 patients) with DR were analyzed.

Acceleration of Hyperspectral Skin Cancer Image Classification through Parallel Machine-Learning Methods.

Hyperspectral imaging (HSI) has become a very compelling technique in different scientific areas; indeed, many researchers use it in the fields of remote sensing, agriculture, forensics, and medicine. In the latter, HSI plays a crucial role as a diagnostic support and for surgery guidance. However, the computational effort in elaborating hyperspectral data is not trivial.

Clinical Features Related to OCT Angiography Artifacts in Patients with Diabetic Macular Edema.

Purpose: To investigate the frequency and type of artifacts on OCT angiography (OCTA) images and the relationship with clinical features in eyes with diabetic macular edema (DME).

Design: Retrospective, cross-sectional comparative study.

Subjects: One hundred ninety-two eyes of 140 patients with DME were included.

Macula vs periphery in diabetic retinopathy: OCT-angiography and ultrawide field fluorescein angiography imaging of retinal non perfusion.

Objectives: To investigate the association between peripheral non-perfusion index (NPI) on ultrawide-field fluorescein angiography (UWF-FA) and quantitative OCT-Angiography (OCT-A) metrics in the macula.

Methods: In total, 48 eyes with UWF-colour fundus photos (CFP), UWF-FA (California, Optos) and OCT-A (Spectralis, Heidelberg) were included. OCT-A (3 × 3 mm) was used to determine foveal avascular zone (FAZ) parameters and vessel density (VD), perfusion density (PD), fractal dimension (FD) on superficial capillary plexus (SCP).

Ambient assisted living for frail people through human activity recognition: state-of-the-art, challenges and future directions.

Ambient Assisted Living is a concept that focuses on using technology to support and enhance the quality of life and well-being of frail or elderly individuals in both indoor and outdoor environments. It aims at empowering individuals to maintain their independence and autonomy while ensuring their safety and providing assistance when needed. Human Activity Recognition is widely regarded as the most popular methodology within the field of Ambient Assisted Living.

LONGITUDINAL MICROVASCULAR AND NEURONAL RETINAL EVALUATION IN PATIENTS WITH DIABETES MELLITUS TYPES 1 AND 2 AND GOOD GLYCEMIC CONTROL.

Purpose: To evaluate microvascular and neuronal changes over 3 years in patients with Type 1/2 diabetes mellitus (DM1/DM2), good metabolic control, and no signs of diabetic retinopathy.

Methods: In this prospective, longitudinal study, 20 DM1, 48 DM2, and 24 controls underwent macular optical coherence tomography and optical coherence tomography angiography at baseline and after 3 years. Following parameters were considered: thickness of the central macula, retinal nerve fiber layer, ganglion cell (GCL+/GCL++) complex; perfusion and vessel density and fractal dimension at the superficial and deep capillary plexuses; choriocapillaris flow deficits; and foveal avascular zone metrics.

Multimodal Retinal Imaging in Patients with Diabetes Mellitus and Association with Cerebrovascular Disease.

Introduction: This study aimed to evaluate the association between macular optical coherence tomography angiography (OCT-A) metrics, characteristics of ultrawide field (UWF) imaging, and cerebrovascular disease in patients with diabetes mellitus (DM) with different stages of diabetic retinopathy (DR).

Methods: 516 eyes of 258 DM patients were enrolled in two centers (Milan and Belfast). UWF color fundus photos (CFPs) were obtained with Optos California (Optos, PLC) and graded for both DR severity and predominantly peripheral lesions presence (>50% of CFP lesions) by two independent graders.

Perceptive SARS-CoV-2 End-To-End Ultrasound Video Classification through X3D and Key-Frames Selection.

The SARS-CoV-2 pandemic challenged health systems worldwide, thus advocating for practical, quick and highly trustworthy diagnostic instruments to help medical personnel. It features a long incubation period and a high contagion rate, causing bilateral multi-focal interstitial pneumonia, generally growing into acute respiratory distress syndrome (ARDS), causing hundreds of thousands of casualties worldwide. Guidelines for first-line diagnosis of pneumonia suggest Chest X-rays (CXR) for patients exhibiting symptoms.

Evaluation of Preprocessing Methods on Independent Medical Hyperspectral Databases to Improve Analysis.

Currently, one of the most common causes of death worldwide is cancer. The development of innovative methods to support the early and accurate detection of cancers is required to increase the recovery rate of patients. Several studies have shown that medical Hyperspectral Imaging (HSI) combined with artificial intelligence algorithms is a powerful tool for cancer detection.

Towards the Simulation of a Realistic Large-Scale Spiking Network on a Desktop Multi-GPU System.

The reproduction of the brain 'sactivity and its functionality is the main goal of modern neuroscience. To this aim, several models have been proposed to describe the activity of single neurons at different levels of detail. Then, single neurons are linked together to build a network, in order to reproduce complex behaviors.

Neural Networks-Based On-Site Dermatologic Diagnosis through Hyperspectral Epidermal Images.

Cancer originates from the uncontrolled growth of healthy cells into a mass. Chromophores, such as hemoglobin and melanin, characterize skin spectral properties, allowing the classification of lesions into different etiologies. Hyperspectral imaging systems gather skin-reflected and transmitted light into several wavelength ranges of the electromagnetic spectrum, enabling potential skin-lesion differentiation through machine learning algorithms.

Deep Convolutional Generative Adversarial Networks to Enhance Artificial Intelligence in Healthcare: A Skin Cancer Application.

In recent years, researchers designed several artificial intelligence solutions for healthcare applications, which usually evolved into functional solutions for clinical practice. Furthermore, deep learning (DL) methods are well-suited to process the broad amounts of data acquired by wearable devices, smartphones, and other sensors employed in different medical domains. Conceived to serve the role of diagnostic tool and surgical guidance, hyperspectral images emerged as a non-contact, non-ionizing, and label-free technology.

Deep learning and lung ultrasound for Covid-19 pneumonia detection and severity classification.

The Covid-19 European outbreak in February 2020 has challenged the world's health systems, eliciting an urgent need for effective and highly reliable diagnostic instruments to help medical personnel. Deep learning (DL) has been demonstrated to be useful for diagnosis using both computed tomography (CT) scans and chest X-rays (CXR), whereby the former typically yields more accurate results. However, the pivoting function of a CT scan during the pandemic presents several drawbacks, including high cost and cross-contamination problems.

Granular layEr Simulator: Design and Multi-GPU Simulation of the Cerebellar Granular Layer.

In modern computational modeling, neuroscientists need to reproduce long-lasting activity of large-scale networks, where neurons are described by highly complex mathematical models. These aspects strongly increase the computational load of the simulations, which can be efficiently performed by exploiting parallel systems to reduce the processing times. Graphics Processing Unit (GPU) devices meet this need providing on desktop High Performance Computing.

Subthreshold Micropulse Laser in Diabetic Macular Edema: 1-Year Improvement in OCT/OCT-Angiography Biomarkers.

Purpose: The aim of this study was to evaluate 1-year quantitative changes in specific inflammatory parameters on optical coherence tomography (OCT) / optical coherence tomography angiography (OCTA) in diabetic macular edema (DME) treated with subthreshold micropulse laser (SMPL).

Methods: Thirty-seven patients / eyes with previously treatment-naïve DME treated with SMPL were prospectively evaluated at 3, 6, and 12 months. Fifteen fellow eyes with only microaneurysms (MAS) not eligible for treatment were controls.

Raman Spectroscopy Reveals That Biochemical Composition of Breast Microcalcifications Correlates with Histopathologic Features.

Breast microcalcifications are a common mammographic finding. Microcalcifications are considered suspicious signs of breast cancer and a breast biopsy is required, however, cancer is diagnosed in only a few patients. Reducing unnecessary biopsies and rapid characterization of breast microcalcifications are unmet clinical needs.

Diabetic macular edema with neuroretinal detachment: OCT and OCT-angiography biomarkers of treatment response to anti-VEGF and steroids.

Purpose: To assess and compare early changes in neuroinflammatory and vascular parameters in diabetic macular edema (DME) with subfoveal neuroretinal detachment (SND) after treatment with intravitreal dexamethasone (DEX-I) and ranibizumab (IVR).

Methods: Thirty-three eyes (33 patients) with treatment naïve DME with SND were retrospectively evaluated at baseline and 2 months after DEX-I (15 eyes) and 1 month after 3 monthly IVR injections (18 eyes). Inclusion criteria were: complete eye examination, good quality OCT and OCT-A images.

Quantitative choriocapillaris evaluation in intermediate age-related macular degeneration by swept-source optical coherence tomography angiography.

Purpose: To investigate choriocapillaris (CC) perfusion, by evaluating flow voids (FV), in eyes with intermediate age-related macular degeneration (iAMD) using swept-source optical coherence tomography angiography (SS-OCT-A).

Methods: Patients with bilateral or unilateral iAMD and normal controls underwent SS-OCT and OCT-A examination. Choriocapillaris (CC) FVs were quantitatively assessed on OCT-A images using matlab (version 2017b; MathWorks, Natick, MA, USA), after a preprocessing aimed at compensating for CC attenuation artefacts.

Accelerating the K-Nearest Neighbors Filtering Algorithm to Optimize the Real-Time Classification of Human Brain Tumor in Hyperspectral Images.

The use of hyperspectral imaging (HSI) in the medical field is an emerging approach to assist physicians in diagnostic or surgical guidance tasks. However, HSI data processing involves very high computational requirements due to the huge amount of information captured by the sensors. One of the stages with higher computational load is the K-Nearest Neighbors (KNN) filtering algorithm.