Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs
The slaughterhouse can act as a valid checkpoint to estimate the prevalence and the economic impact of diseases in farm animals. At present, scoring lesions is a challenging and time-consuming activity, which is carried out by veterinarians serving the slaughter chain. Over recent years, artificial...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/11/11/3290 |
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| author | Lorenzo Bonicelli Abigail Rose Trachtman Alfonso Rosamilia Gaetano Liuzzo Jasmine Hattab Elena Mira Alcaraz Ercole Del Negro Stefano Vincenzi Andrea Capobianco Dondona Simone Calderara Giuseppe Marruchella |
| author_facet | Lorenzo Bonicelli Abigail Rose Trachtman Alfonso Rosamilia Gaetano Liuzzo Jasmine Hattab Elena Mira Alcaraz Ercole Del Negro Stefano Vincenzi Andrea Capobianco Dondona Simone Calderara Giuseppe Marruchella |
| author_sort | Lorenzo Bonicelli |
| collection | DOAJ |
| description | The slaughterhouse can act as a valid checkpoint to estimate the prevalence and the economic impact of diseases in farm animals. At present, scoring lesions is a challenging and time-consuming activity, which is carried out by veterinarians serving the slaughter chain. Over recent years, artificial intelligence(AI) has gained traction in many fields of research, including livestock production. In particular, AI-based methods appear able to solve highly repetitive tasks and to consistently analyze large amounts of data, such as those collected by veterinarians during postmortem inspection in high-throughput slaughterhouses. The present study aims to develop an AI-based method capable of recognizing and quantifying enzootic pneumonia-like lesions on digital images captured from slaughtered pigs under routine abattoir conditions. Overall, the data indicate that the AI-based method proposed herein could properly identify and score enzootic pneumonia-like lesions without interfering with the slaughter chain routine. According to European legislation, the application of such a method avoids the handling of carcasses and organs, decreasing the risk of microbial contamination, and could provide further alternatives in the field of food hygiene. |
| first_indexed | 2024-03-10T05:45:52Z |
| format | Article |
| id | doaj.art-220957cc78744aeb8e271664e45828b6 |
| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-03-10T05:45:52Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Animals |
| spelling | doaj.art-220957cc78744aeb8e271664e45828b62023-11-22T22:08:23ZengMDPI AGAnimals2076-26152021-11-011111329010.3390/ani11113290Training Convolutional Neural Networks to Score Pneumonia in Slaughtered PigsLorenzo Bonicelli0Abigail Rose Trachtman1Alfonso Rosamilia2Gaetano Liuzzo3Jasmine Hattab4Elena Mira Alcaraz5Ercole Del Negro6Stefano Vincenzi7Andrea Capobianco Dondona8Simone Calderara9Giuseppe Marruchella10AImageLab, University of Modena and Reggio Emilia, Via Vivarelli 10/1, 41125 Modena, ItalyFaculty of Veterinary Medicine, University of Teramo, Loc. Piano d’Accio, 64100 Teramo, ItalyDepartment of Veterinary Public Health, Azienda Unità Sanitaria Locale di Modena, via S. Giovanni del Cantone 23, 41121 Modena, ItalyDepartment of Veterinary Public Health, Azienda Unità Sanitaria Locale di Modena, via S. Giovanni del Cantone 23, 41121 Modena, ItalyFaculty of Veterinary Medicine, University of Teramo, Loc. Piano d’Accio, 64100 Teramo, ItalyFaculty of Veterinary Medicine, University of Teramo, Loc. Piano d’Accio, 64100 Teramo, ItalyAImageLab, University of Modena and Reggio Emilia, Via Vivarelli 10/1, 41125 Modena, ItalyFarm4Trades.r.l., Via IV Novembre, 66041 Atessa, ItalyFarm4Trades.r.l., Via IV Novembre, 66041 Atessa, ItalyAImageLab, University of Modena and Reggio Emilia, Via Vivarelli 10/1, 41125 Modena, ItalyFaculty of Veterinary Medicine, University of Teramo, Loc. Piano d’Accio, 64100 Teramo, ItalyThe slaughterhouse can act as a valid checkpoint to estimate the prevalence and the economic impact of diseases in farm animals. At present, scoring lesions is a challenging and time-consuming activity, which is carried out by veterinarians serving the slaughter chain. Over recent years, artificial intelligence(AI) has gained traction in many fields of research, including livestock production. In particular, AI-based methods appear able to solve highly repetitive tasks and to consistently analyze large amounts of data, such as those collected by veterinarians during postmortem inspection in high-throughput slaughterhouses. The present study aims to develop an AI-based method capable of recognizing and quantifying enzootic pneumonia-like lesions on digital images captured from slaughtered pigs under routine abattoir conditions. Overall, the data indicate that the AI-based method proposed herein could properly identify and score enzootic pneumonia-like lesions without interfering with the slaughter chain routine. According to European legislation, the application of such a method avoids the handling of carcasses and organs, decreasing the risk of microbial contamination, and could provide further alternatives in the field of food hygiene.https://www.mdpi.com/2076-2615/11/11/3290pigslaughterhousepneumoniascoring methodsartificial intelligencedeep learning |
| spellingShingle | Lorenzo Bonicelli Abigail Rose Trachtman Alfonso Rosamilia Gaetano Liuzzo Jasmine Hattab Elena Mira Alcaraz Ercole Del Negro Stefano Vincenzi Andrea Capobianco Dondona Simone Calderara Giuseppe Marruchella Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs Animals pig slaughterhouse pneumonia scoring methods artificial intelligence deep learning |
| title | Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs |
| title_full | Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs |
| title_fullStr | Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs |
| title_full_unstemmed | Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs |
| title_short | Training Convolutional Neural Networks to Score Pneumonia in Slaughtered Pigs |
| title_sort | training convolutional neural networks to score pneumonia in slaughtered pigs |
| topic | pig slaughterhouse pneumonia scoring methods artificial intelligence deep learning |
| url | https://www.mdpi.com/2076-2615/11/11/3290 |
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