Paolo Zaffino

Paolo Zaffino
Universita' degli Studi "Magna Græcia" di Catanzaro | Università Magna Græcia di Catanzaro · Department of Experimental and Clinical Medicine "Gaetano Salvatore"

PhD

About

48
Publications
11,445
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
764
Citations
Additional affiliations
August 2019 - present
Universita' degli Studi "Magna Græcia" di Catanzaro
Position
  • Professor (Assistant)
Description
  • Assistant Professor of Biomedical Engineering
October 2015 - present
Universita' degli Studi "Magna Græcia" di Catanzaro
Position
  • Contractor Professor
Description
  • "Automazione, Organizzazione e Sicurezza Sanitaria"
September 2015 - July 2019
Universita' degli Studi "Magna Græcia" di Catanzaro
Position
  • PostDoc Position
Education
April 2012 - March 2015
Universita' degli Studi "Magna Græcia" di Catanzaro
Field of study
  • Biomedical Engineering
October 2009 - October 2011
October 2006 - October 2009

Publications

Publications (48)
Article
Full-text available
Coronary Angiography (CA) is the standard of reference to diagnose coronary artery disease. Yet, only a portion of the information it conveys is usually used. Quantitative Coronary Angiography (QCA) reliably contributes to improving the measurable assessment of CA. In this work, we developed a new software, CoroFinder, able to automatically identif...
Chapter
Microarray is a powerful technology that enables the monitoring of expression levels for thousands of genes simultaneously, providing scientists with a full overview about DNA and RNA investigation. The process is made of three main phases: interaction with biological samples, data extraction, and data analysis. In particular, the data extraction p...
Article
Full-text available
Purpose: Adaptive proton therapy (APT) of lung cancer patients requires frequent volumetric imaging of diagnostic quality. Cone-beam CT (CBCT) can provide these daily images, but x-ray scattering limits CBCT-image quality and hampers dose calculation accuracy. The purpose of this study was to generate CBCT-based synthetic CTs using a deep convolut...
Article
Full-text available
Recently, deep learning (DL)‐based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by grouping them into three categories, according to their clinical applications: I) to replace CT in magnetic res...
Article
Full-text available
The coronavirus disease 19 (COVID-19) pandemic is having a dramatic impact on society and healthcare systems. In this complex scenario, lung computerized tomography (CT) may play an important prognostic role. However, datasets released so far present limitations that hamper the development of tools for quantitative analysis. In this paper, we prese...
Article
Full-text available
Background This study aims to examine the underlying associations between eating, affective and metacognitive symptoms in patients with binge eating disorder (BED) through network analysis (NA) in order to identify key variables that may be considered the target for psychotherapeutic interventions. Methods A total of 155 patients with BED complete...
Preprint
Full-text available
Recently, deep learning (DL)-based methods for the generation of synthetic computed tomography (sCT) have received significant research attention as an alternative to classical ones. We present here a systematic review of these methods by grouping them into three categories, according to their clinical applications: I) to replace CT in magnetic res...
Preprint
Full-text available
Background: This study aims to examine the underlying associations between eating, affective and metacognitive symptoms in patients with binge eating disorder (BED) through network analysis (NA), in order to identify key variables that may be considered the target for psychotherapeutic interventions. Methods: One hundred and fifty-five patients wit...
Preprint
Full-text available
Background: This study aims to examine the underlying associations between eating, affective and metacognitive symptoms in patients with binge eating disorder (BED) through network analysis (NA), in order to identify key variables that may be considered the target for psychotherapeutic interventions. Methods: One hundred and fifty-five patients wit...
Article
Full-text available
Interaction between medical image platform and external environment is a desirable feature in several clinical, research, and educational scenarios. In this work, the integration between 3D Slicer package and Arduino board is introduced, enabling a simple and useful communication between the two software/hardware platforms. The open source extensio...
Article
Full-text available
CBCT- and MR-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep convolutional neural networks (DCNN). In this study, we compared sCTs based on CBCTs and MRs for head and neck cancer patients in terms of image quality a...
Article
With the advent of Minimally Invasive Surgery (MIS), intra-operative imaging has become crucial for surgery and therapy guidance, allowing to partially compensate for the lack of information typical of MIS. This paper reviews the advancements in both classical (i.e. ultrasounds, X-ray, optical coherence tomography and magnetic resonance imaging) an...
Article
Full-text available
In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation decisions. Image quality deficiencies though, hamper dose calculation accuracy and make corrections o...
Article
Full-text available
The intricate relationships between innate immunity and brain diseases raise increased interest across the wide spectrum of neurodegenerative and neuropsychiatric disorders. Barriers, such as the blood–brain barrier, and innate immunity cells such as microglia, astrocytes, macrophages, and mast cells are involved in triggering disease events in the...
Chapter
Radiation therapy is one of the most important strategies for treating patients with tumor. The rationale is to deliver high radiation doses to the tumor in order to damage its DNA while sparing, at the same time, healthy tissues. In order to optimize such a process, biomedical images play a fundamental role; in particular, Magnetic Resonance (MR)...
Article
Full-text available
External-beam radiotherapy followed by High Dose Rate (HDR) brachytherapy is the standard-of-care for treating gynecologic cancers. The enhanced soft-tissue contrast provided by Magnetic Resonance Imaging (MRI) makes it a valuable imaging modality for diagnosing and treating these cancers. However, in contrast to Computed Tomography (CT) imaging, t...
Article
Purpose: The first aim of this work is to present a novel deep convolution neural network (DCNN) multiplane approach and compare it to single-plane prediction of synthetic computed tomography (sCT) by using the real computed tomography (CT) as ground truth. The second aim is to demonstrate the feasibility of magnetic resonance imaging (MRI)-based...
Article
The data of literature are discordant about the role of mast cells in different types of neoplasms. In this paper the authors propose the hypothesis that tumor-associated mast cells may switch to different polarization states, conditioning the immunogenic capacities of the different neoplasms. Anti-inflammatory polarized mast cells should express c...
Article
Purpose In radiation therapy, a key step for a successful cancer treatment is image-based treatment planning. One objective of the planning phase is the fast and accurate segmentation of organs at risk and target structures from medical images. However, manual delineation of organs, which is still the gold standard in many clinical environments, is...
Article
Full-text available
Recent studies have clarified many still unknown aspects related to innate immunity and the blood-brain barrier relationship. They have also confirmed the close links between effector immune system cells, such as granulocytes, macrophages, microglia, natural killer cells and mast cells, and barrier functionality. The latter, in turn, is able to inf...
Chapter
The assessment of vascular complexity in the lower limbs provides important information about peripheral artery diseases, with a relevant impact on both therapeutic decisions and on prognostic estimation. Currently, the evaluation is carried out by visual inspection of cine-angiograms, which is largely operator-dependent. An automatic image analysi...
Preprint
Full-text available
Multi Atlas Based Segmentation (MABS) uses a database of atlas images, and an atlas selection process is used to choose an atlas subset for registration and voting. In the current state of the art, atlases are chosen according to a similarity criterion between the target subject and each atlas in the database. In this paper, we propose a new concep...
Article
Full-text available
Multi Atlas Based Segmentation (MABS) uses a database of atlas images, and an atlas selection process is used to choose an atlas subset for registration and voting. In the current state of the art, atlases are chosen according to a similarity criterion between the target subject and each atlas in the database. In this paper, we propose a new concep...
Article
Full-text available
Purpose: Automated delineation of structures and organs is a key step in medical imaging. However, due to the large number and diversity of structures and the large variety of segmentation algorithms a consensus is lacking as to which automated segmentation method works best for certain applications. Segmentation challenges are a good approach for...
Article
Objectives: Atlas-based automatic segmentation (ABAS) addresses the challenges of accuracy and reliability in manual segmentation. We aim to evaluate the contribution of specific-purpose in ABAS of breast cancer (BC) patients with respect to generic-purpose libraries. Materials and methods: One generic-purpose and 9 specific-purpose libraries, s...
Conference Paper
Full-text available
During the last years Deep Learning and especially Convolutional Neural Networks (CNN) have set new standards for different computer vision tasks like image classification and semantic segmentation. In this paper, a CNN for 3D volume segmentation based on recently introduced deep learning components will be presented. In addition to using image pat...
Article
Purpose: Multiatlas based segmentation is largely used in many clinical and research applications. Due to its good performances, it has recently been included in some commercial platforms for radiotherapy planning and surgery guidance. Anyway, to date, a software with no restrictions about the anatomical district and image modality is still missing...
Article
Purpose:In this work we present the validation of Plastimatch MABS, an open source software for multi atlas based segmentation of medical images. Methods:The validation was performed on two different clinical datasets: 1) 25 CT image volumes of patients treated for H&N cancer; 2) 20 MRI series of patients having a neurological diagnosis. For the fi...
Article
To improve the contouring of clinical target volume for the radiotherapy of neck Hodgkin/non-Hodgkin lymphoma by localizing the prechemotherapy gross target volume onto the simulation computed tomography using [(18)F]-fluorodeoxyglucose positron emission tomography/computed tomography. The gross target volume delineated on prechemotherapy [(18)F]-f...
Article
Automated segmentation is a frequently applied task in the course of medical imaging. Furthermore, it is a substantial component of image-guided radiotherapy. Atlas based segmentation is one of the most frequently used approach for automated segmentation. Especially for multi-atlas based segmentation, segmentation quality and speed largely depends...
Article
Purpose To obtain a contrasted image of the tumor region during the setup for proton therapy in lung patients, by using proton radiography and x-ray computed tomography (CT) prior knowledge. Methods and Materials Six lung cancer patients' CT scans were preprocessed by masking out the gross tumor volume (GTV), and digitally reconstructed radiograph...
Article
Full-text available
Accurate delineation of organs at risk (OARs) is a precondition for intensity modulated radiation therapy. However, manual delineation of OARs is time consuming and prone to high interobserver variability. Because of image artifacts and low image contrast between different structures, however, the number of available approaches for autosegmentation...
Conference Paper
Purpose/Objective: The aim of this work is to design and test different atlas selection strategies to optimize multi atlas based segmentation (MABS). The methodology was implemented and evaluated in the framework of head and neck radiotherapy to allow automatic contouring of OARs. Materials and Methods: MABS methods require the availability of...

Projects

Project (1)
Project
Plastimatch is an open source software for image computation. Our main focus is high-performance volumetric registration, segmentation, and image processing of volumetric medical images. Plastimatch is developed by Dr. Gregory C. Sharp and his group at Massachusetts General Hospital, Boston. www.plastimatch.org