AIMC Topic: Dogs

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Machine learning based diagnostics of veterinary cancer on ultrasound and optical imaging data.

The veterinary quarterly
Study advances current diagnostic efficiency of canine/feline (sub-)cutaneous tumors using machine learning and multimodal imaging data. White light (WL), fluorescence (FL) and ultrasound (US) imaging were combined into hybrid approaches to different...

Beauty versus the beast: The UK public prefers less-extreme body shapes in brachycephalic dog breeds.

The Veterinary record
BACKGROUND: Brachycephalic dog breeds often exhibit a suite of extreme conformations linked with several severe and long-term disorders. Despite this, ownership levels of brachycephalic breeds remain high internationally, with physical appearance bei...

Deep Learning Can be Used to Classify the Disease Status of the Canine Middle Ear From Computed Tomographic Images.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Middle ear disease occurs frequently in dogs. CT has proven to be an excellent diagnostic tool for detecting middle ear structures, helping to achieve rapid and accurate diagnoses. Deep learning techniques are now widely used in CT scan-based human m...

LiDSCUNet++: A lightweight depth separable convolutional UNet++ for vertebral column segmentation and spondylosis detection.

Research in veterinary science
Accurate computer-aided diagnosis systems rely on precise segmentation of the vertebral column to assist physicians in diagnosing various disorders. However, segmenting spinal disks and bones becomes challenging in the presence of abnormalities and c...

Annotating neurophysiologic data at scale with optimized human input.

Journal of neural engineering
Neuroscience experiments and devices are generating unprecedented volumes of data, but analyzing and validating them presents practical challenges, particularly in annotation. While expert annotation remains the gold standard, it is time consuming to...

Novel robotic tools used for the detection of faecal shedding of Escherichia coli resistant to critically important antimicrobials in healthy dogs.

Veterinary microbiology
Escherichia coli recovered from dogs with clinical conditions such as urinary tract infections are often used to assess populations for resistance to critically important antimicrobials (CIAs). Despite the potential importance of such strains, the nu...

Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.

Scientific reports
Canine/feline (sub-)cutaneous tumors, which include lipomas, mastocytomas and soft tissue sarcomas, introduce diagnostic challenges due to inherent tissue heterogeneity, accompanied by diverse clinical pathogenesis. Current study integrates conventio...

Machine learning analysis of factors contributing to hypotension after lumbosacral epidural anaesthesia in dogs undergoing abdominal surgery.

Scientific reports
The incidence of hypotension after a lumbosacral epidural in dogs depends on the volume of local anaesthetic administered. So far, there are no reports comparing both methods used to calculate this volume-body weight (BW) and occipito-coccygeal lengt...

A Pilot Study on Using an Artificial Intelligence Algorithm to Identify Urolith Composition through Abdominal Radiographs in the Dog.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
In small animal practice, patients often present with urinary lithiasis, and prediction of urolith composition is essential to determine the appropriate treatment. Through abdominal radiographs, the composition of mineral radiopaque uroliths can be d...

A Veterinary DICOM-Based Deep Learning Denoising Algorithm Can Improve Subjective and Objective Brain MRI Image Quality.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
In this analytical cross-sectional method comparison study, we evaluated brain MR images in 30 dogs and cats with and without using a DICOM-based deep-learning (DL) denoising algorithm developed specifically for veterinary patients. Quantitative comp...