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Veterinary Sciences
Special Issues
Veterinary Digital and Computer-Aided Pathology Systems
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Veterinary Digital and Computer-Aided Pathology Systems

A special issue of Veterinary Sciences (ISSN 2306-7381).

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 8403

Special Issue Editors

Dr. Giovanni Pietro Burrai

E-Mail Website
Guest Editor
Department of Veterinary Medicine, University of Sassari, Via Vienna, 2-07100 Sassari, Italy
Interests: canine and feline mammary tumors; papillomavirus-related tumors; immunohistochemistry; digital pathology
Dr. Barbara Bacci

E-Mail Website
Guest Editor
Department of Veterinary Medical Sciences, University of Bologna Via Tolara di sopra, 50, Ozzano dell’Emilia, 40064 Bologna, Italy
Interests: canine and feline pathology; equine pathology; oncology; immunohistochemistry; digital pathology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Digital pathology is now a remarkable field of innovation in the current diagnostic setting, with education and research changing the paradigm of microscope-based pathology. At present, digitized pathologic images stored in the cloud can be easily transmitted and further analyzed by computer-aided pathology systems making use of technologies such as machine learning algorithms and deep neural networks helping in the disease classification, biomarker discovery, and prognosis prediction. In the turnaround of this digital revolution, the aim of this Special Issue is to publish original research works and reviews on the topic of veterinary digital pathology and applied artificial intelligence systems.

Dr. Giovanni Pietro Burrai
Dr. Barbara Bacci
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Veterinary Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2100 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • animal disease
  • digital pathology
  • artificial intelligence
  • tumors

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Published Papers (2 papers)

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Research

16 pages, 4954 KiB  
Article
Evaluation of the COVID-19 Lockdown-Adapted Online Methodology for the Cytology and Histology Course as Part of the Degree in Veterinary Medicine
by Ana Balseiro, Claudia Pérez-Martínez, Paulino de Paz and María José García Iglesias
Vet. Sci. 2022, 9(2), 51; https://doi.org/10.3390/vetsci9020051 - 27 Jan 2022
Cited by 2 | Viewed by 3092
Abstract
The COVID-19 pandemic and lockdown brought numerous teaching challenges requiring innovative approaches to teaching and learning, including novel modes of content delivery, virtual classrooms, and online assessment schemes. The aim of this study is to describe and assess the efficacy of the methods [...] Read more.
The COVID-19 pandemic and lockdown brought numerous teaching challenges requiring innovative approaches to teaching and learning, including novel modes of content delivery, virtual classrooms, and online assessment schemes. The aim of this study is to describe and assess the efficacy of the methods implemented at the University of León (Spain) to adapt to lockdowns in the context of the Cytology and Histology (CH) course for veterinary medicine undergraduate students. To evaluate the success of lockdown-adapted methodologies, we used inferential statistical analysis to compare the academic outcomes of two cohorts: 2018–2019 (traditional face-to-face—presential—learning and evaluation) and 2019–2020 (some face-to-face and some online lockdown-adapted learning and online lockdown-adapted evaluation). This analysis considered scores in both theoretical and practical exams and students’ final subject score. We also evaluated the number of logs onto the Moodle platform throughout the 2019–2020 period, as well as performing a student satisfaction survey in both courses. The use of explanatory pre-recorded lectures, continuous online self-assessment tests, and virtual microscopy (VM) may have produced significant improvements in the acquisition of histology competencies among students in the lockdown cohort. However, we need to implement further strategies to improve the assessment of students’ true level of knowledge acquisition. According to the student feedback, VM is a well-accepted resource that is perceived as a flexible and enjoyable tool to use. However, while students found that the resource enhances their ability to learn about microscopic structures, they felt that it should not completely replace optical microscopy. Full article
(This article belongs to the Special Issue Veterinary Digital and Computer-Aided Pathology Systems)
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9 pages, 780 KiB  
Article
Morphometrical Study of the European Shorthair Cat Skull Using Computed Tomography
by Joana Ramos, Inês Viegas, Hugo Pereira and João Filipe Requicha
Vet. Sci. 2021, 8(8), 161; https://doi.org/10.3390/vetsci8080161 - 10 Aug 2021
Cited by 8 | Viewed by 4378
Abstract
This study aimed to perform a morphometric analysis of the skull of the European shorthair cat by using computed tomographic images. Thirty-seven computed tomography (CT) studies of healthy cats’ heads were used for linear measurements and index calculations of the skull and cranium. [...] Read more.
This study aimed to perform a morphometric analysis of the skull of the European shorthair cat by using computed tomographic images. Thirty-seven computed tomography (CT) studies of healthy cats’ heads were used for linear measurements and index calculations of the skull and cranium. The following values were determined: skull length = 8.94 ± 0.45 cm, cranial length = 8.21 ± 0.42 cm, nasal length = 0.73 ± 0.17 cm, cranial width = 4.28 ± 0.26 cm, cranial index = 52.18 ± 3.75%, internal height of cranium = 2.88 ± 0.29 cm, external height of cranium = 3.35 ± 0.12 cm, internal length of the cranium = 5.53 ± 0.28 cm, external length of the cranium = 6.32 ± 0.28 cm, internal cranium index = 45.62 ± 4.77%, external cranium index = 53.06 ± 2.07%, internal cranium and skull index = 61.93 ± 2.38%, external cranium and skull index = 70.70 ± 1.72%, width of the foramen magnum = 1.34 ± 0.07 cm, height of the foramen magnum = 1.01 ± 0.09 cm, and foramen magnum index = 75.37 ± 5.76%. It was also found that the population was homogeneous, with the exception of nasal length (NL), and that there was a sexual dimorphism present, with males exhibiting higher dimensions. This work contributed to characterizing the morphometry of the cranium and skull of the domestic cat, a knowledge of utmost importance for the diagnosis and treatment of conditions affecting this complex anatomical region. Full article
(This article belongs to the Special Issue Veterinary Digital and Computer-Aided Pathology Systems)
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