Employing deep convolutional neural networks for segmenting the medial retropharyngeal lymph nodes in CT studies of dogs.

While still in its infancy, the application of deep convolutional neural networks in veterinary diagnostic imaging is a rapidly growing field. The preferred deep learning architecture to be employed is convolutional neural networks, as these provide the structure preferably used for the analysis of medical images. With this retrospective exploratory study, the applicability of such networks for the task of delineating certain organs with respect to their surrounding tissues was tested.

Comparison between computed tomography and (99m)TC- pertechnetate scintigraphy characteristics of the thyroid gland in cats with hyperthyroidism.

Scintigraphy is currently the reference standard for diagnosing feline hyperthyroidism; however, computed tomography (CT) is more widely available in veterinary practice. The purposes of this prospective study were to describe the CT appearance of thyroid glands in cats with hyperthyroidism and compare CT findings with findings from (99m) Tc-pertechnetate scintigraphy. Twenty-five adult hyperthyroid cats were included.