AI Medical Compendium Topic

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Cats

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Infrared and visible image fusion method of dual NSCT and PCNN.

PloS one
To solve the problem that the details of fusion images are not retained well and the information of feature targets is incomplete, we proposed a new fusion method of infrared (IR) and visible (VI) image-IR and VI image fusion method of dual non-subsa...

Robot companion cats for people at home with dementia: A qualitative case study on companotics.

Dementia (London, England)
The use of robot companion pets for people in care homes has been extensively studied. The results are largely positive and suggest that they are valuable in enhancing wellbeing, communication and behavioural aspects. However, there has been little r...

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

Parasites & vectors
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 s...

The CPGs for Limbed Locomotion-Facts and Fiction.

International journal of molecular sciences
The neuronal networks that generate locomotion are well understood in swimming animals such as the lamprey, zebrafish and tadpole. The networks controlling locomotion in tetrapods remain, however, still enigmatic with an intricate motor pattern requi...

Quantifying finer-scale behaviours using self-organising maps (SOMs) to link accelerometery signatures with behavioural patterns in free-roaming terrestrial animals.

Scientific reports
Collecting quantitative information on animal behaviours is difficult, especially from cryptic species or species that alter natural behaviours under observation. Using harness-mounted tri-axial accelerometers free-roaming domestic cats (Felis Catus)...

Classifying Retinal Degeneration in Histological Sections Using Deep Learning.

Translational vision science & technology
PURPOSE: Artificial intelligence (AI) techniques are increasingly being used to classify retinal diseases. In this study we investigated the ability of a convolutional neural network (CNN) in categorizing histological images into different classes of...

Integrative measurement analysis via machine learning descriptor selection for investigating physical properties of biopolymers in hairs.

Scientific reports
Integrative measurement analysis of complex subjects, such as polymers is a major challenge to obtain comprehensive understanding of the properties. In this study, we describe analytical strategies to extract and selectively associate compositional i...

Adaptive Modular Convolutional Neural Network for Image Recognition.

Sensors (Basel, Switzerland)
Image recognition has long been one of the research hotspots in computer vision tasks. The development of deep learning is rapid in recent years, and convolutional neural networks usually need to be designed with fixed resources. If sufficient resour...

Deep learning in veterinary medicine, an approach based on CNN to detect pulmonary abnormalities from lateral thoracic radiographs in cats.

Scientific reports
Thoracic radiograph (TR) is a complementary exam widely used in small animal medicine which requires a sharp analysis to take full advantage of Radiographic Pulmonary Pattern (RPP). Although promising advances have been made in deep learning for vete...

Study on image data cleaning method of early esophageal cancer based on VGG_NIN neural network.

Scientific reports
In order to clean the mislabeled images in the esophageal endoscopy image data set, we designed a new neural network VGG_NIN. Based on the new neural network structure, we developed a method to clean the mislabeled images in the esophageal endoscopy ...