Automated Diagnosis of Canine Gastrointestinal Parasites Using Image Analysis

Inácio, Sandra Valéria; Gomes, Jancarlo Ferreira; Falcão, Alexandre X.; Suzuki, Celso Tetsuo Nagase; Nagata, Walter Bertequini; Loiola, Saulo Hudson Nery; Santos, Bianca Martins dos; Soares, Felipe Augusto; Rosa, Stefani Laryssa; Baptista, Carolina Beatriz; Alves, Graziella Borges; Bresciani, Kátia Denise Saraiva

doi:10.3390/pathogens9020139

Cited by 16 publications

(11 citation statements)

References 31 publications

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“…A recent study applied a computer vision plus a support vector machine for detection of canine intestinal parasites and evaluated its capability with Ancylostoma eggs, Toxocara eggs, Trichuris eggs and Giardia cysts [21]. In the first step of their process, images were segmented into blobs using a combination of color thresholding and other computer vision techniques.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm

et al. 2020

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Background: Fecal examination is an important component of routine companion animal wellness exams. Sensitivity and specificity of fecal examinations, however, are influenced by sample preparation methodologies and the level of training and experience of personnel who read fecal slides. The VETSCAN IMAGYST system consists of three components: a sample preparation device, a commercially available scanner, and an analysis software. The VETSCAN IMAGYST automated scanner and cloud-based, deep learning algorithm, locates, classifies, and identifies parasite eggs found on fecal microscopic slides. The main study objectives were (i) to qualitatively evaluate the capabilities of the VETSCAN IMAGYST screening system and (ii) to assess and compare the performance of the VETSCAN IMAGYST fecal preparation methods to conventional fecal flotation techniques. Methods: To assess the capabilities of VETSCAN IMAGYST screening components, fecal slides were prepared by the VETSCAN IMAGYST centrifugal and passive flotation techniques with 100 pre-screened fecal samples collected from dogs and cats and examined by both the algorithm and parasitologists. To determine the diagnostic sensitivity and specificity of the VETSCAN IMAGYST sample preparation techniques, fecal flotation slides were prepared by four different techniques (VETSCAN IMAGYST centrifugal and passive flotations, conventional centrifugal flotation, and passive flotation using OVASSAY ® Plus) and examined by parasitologists. Additionally, required sample preparation and scanning times were estimated on a subset of samples to evaluate VETSCAN IMAGYST ease-of-use. Results: The algorithm performance of the VETSCAN IMAGYST closely matched that of the parasitologists, with Pearsonʼs correlation coefficient (r) ranging from 0.83-0.99 across four taxa of parasites, Ancylostoma, Toxocara, Trichuris and Taeniidae. Both VETSCAN IMAGYST centrifugal and passive flotation methods correlated well with conventional preparation methods on all targeted parasites (diagnostic sensitivity of 75.8-100%, specificity of 91.8-100%, qualitative agreement between methods of 93.8-94.5%). Sample preparation, slide scan and image analysis were completed within 10-14 min by VETSCAN IMAGYST centrifugal and passive flotations, respectively. Conclusions: The VETSCAN IMAGYST scanning system with the VETSCAN IMAGYST sample preparation methods demonstrated a qualitative match in comparison to the results of parasitologists' examinations with conventional fecal

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Section: Discussionmentioning

confidence: 99%

Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm

et al. 2020

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“…The VETSCAN IMAGYST system has previously been described [ 39 ]. Briefly, slides with fecal samples were read by the Motic EasyScan One digital slide scanner (Motic, Kowloon Bay, Hong Kong), which provided 40× effective resolution.…”

Section: Methodsmentioning

confidence: 99%

Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm

et al. 2021

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Background Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, their accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST system was developed to provide simpler and easier fecal examinations which are less influenced by examiners’ skills. This system consists of three components: a sample preparation device, an automated microscope scanner, and analysis software. The objectives of this study were to qualitatively evaluate the performance of the VETSCAN IMAGYST system on feline parasites (Ancylostoma and Toxocara cati) and protozoan parasites (Cystoisospora and Giardia) and to assess and compare the performance of the VETSCAN IMAGYST centrifugal flotation method to reference centrifugal and passive flotation methods. Methods To evaluate the diagnostic performance of the scanning and algorithmic components of the VETSCAN IMAGYST system, fecal slides were prepared by the VETSCAN IMAGYST centrifugal flotation technique with pre-screened fecal samples collected from dogs and cats and examined by both an algorithm and parasitologists. To assess the performance of the VETSCAN IMAGYST centrifugal flotation technique, diagnostic sensitivity and specificity were calculated and compared to those of conventional flotation techniques. Results The performance of the VETSCAN IMAGYST algorithm closely correlated with evaluations by parasitologists, with sensitivity of 75.8–100% and specificity of 93.1-100% across the targeted parasites. For samples with 50 eggs or less per slide, Lin’s concordance correlation coefficients ranged from 0.70 to 0.95 across the targeted parasites. The results of the VETSCAN IMAGYST centrifugal flotation method correlated well with those of the conventional centrifugal flotation method across the targeted parasites: sensitivity of 65.7–100% and specificity of 97.6–100%. Similar results were observed for the conventional passive flotation method compared to the conventional centrifugal flotation method: sensitivity of 56.4–91.7% and specificity of 99.4–100%. Conclusions The VETSCAN IMAGYST scanning and algorithmic systems with the VETSCAN IMAGYST fecal preparation technique demonstrated a similar qualitative performance to the parasitologists’ examinations with conventional fecal flotation techniques. Given the deep learning nature of the VETSCAN IMAGYST system, its performance is expected to improve over time, enabling it to be utilized in veterinary clinics to perform fecal examinations accurately and efficiently.

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“…The VETSCAN IMAGYST system has previously been described [39]. Brie y, slides with fecal samples were read by the Motic EasyScan One ® digital slide scanner (Motic, Kowloon Bay, Hong Kong) that provided 40x effective resolution.…”

Section: Vetscan Imagyst Scanner and Algorithmmentioning

confidence: 99%

“…Of note, Giardia has been identi ed as a particularly di cult parasite to diagnose by coprology in veterinary practices [36]. Computerbased algorithms to identify parasites in fecal examinations have recently been developed and introduced with the aim to improve the accuracy and consistency of diagnosing parasitic diseases in dogs and cats [39][40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm

Nagamori¹,

Sedlak

DeRosa

et al. 2021

Preprint

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Background: Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, the accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST system was developed to provide simpler and easier fecal examinations which are less influenced by examiners’ skills. This system consists of three components: a sample preparation device, an automated microscopic scanner, and an analysis software. The objectives of this study were to qualitatively evaluate the performance of the VETSCAN IMAGYST system on feline parasites (Ancylostoma and Toxocara cati) and protozoan parasites (Cystoisospora and Giardia) and to assess and compare the performance of the VETSCAN IMAGYST centrifugal flotation method to reference centrifugal and passive flotation methods.Methods: To evaluate the diagnostic performance of the scanning and algorithmic components of the VETSCAN IMAGYST system, fecal slides were prepared by the VETSCAN IMAGYST centrifugal flotation technique with pre-screened fecal samples collected from dogs and cats and examined by both an algorithm and parasitologist. To assess the performance of the VETSCAN IMAGYST centrifugal flotation technique, diagnostic sensitivity and specificity were calculated and compared to conventional flotation techniques.Results: The performance of the VETSCAN IMAGYST algorithm closely correlated with evaluations by parasitologists, with sensitivity of 75.8-100% and specificity of 93.1-100% across the targeted parasites. For samples with 50 eggs or less per slide, Lin’s concordance correlation coefficients (ρc) ranged from 0.70 to 0.95 across the targeted parasites. The VETSCAN IMAGYST centrifugal flotation method correlated well with the conventional centrifugal flotation method across the targeted parasites: sensitivity of 65.7-100% and specificity of 97.6-100%. Similar results were observed for the conventional passive flotation method compared to the conventional centrifugal flotation method; sensitivity of 56.4-91.7% and specificity of 99.4-100%.Conclusions: The VETSCAN IMAGYST scanning and algorithmic systems with the VETSCAN IMAGYST fecal preparation technique demonstrated a similar qualitative performance to the results of parasitologists’ examinations with conventional fecal flotation techniques. Given the deep learning nature of the VETSCAN IMAGYST system, its performance is expected to improve over time, enabling it to be utilized in veterinary clinics to perform fecal examinations accurately and efficiently.

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Automated Diagnosis of Canine Gastrointestinal Parasites Using Image Analysis

Cited by 16 publications

References 31 publications

Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm

Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm

Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm

Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm

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