Positron Emission Tomography (PET) is being widely used in veterinary

medicine in recent years. Although it was limited to small animals because of its

classical design and the large amount of radionuclide doses required, PET imaging in

horses became possible with the introduction of a portable PET scanner developed

by Brain Biosciences Inc. It was observed that this new modality could capture

abnormalities like lesions that Computed Tomography (CT), Magnetic Resonance

Imaging (MRI) and other modalities could not. Since 2016, PET imaging in horses

is being studied and analysed.

While PET provides functional information characterizing the activity of lesions,

it is useful to combine information from other modalities like CT and match

the structural information to develop an accurate spatial representation of the data.

Since biochemical changes occur much earlier than structural changes, this helps

detect lesions and tumours during the early stages. Multimodal image registration

is used to achieve this goal. A series of steps are proposed to automate the process

of registration of equine PET and CT images. Multimodal image registration using landmark-based and intensity-based techniques are studied. It is observed

that a few tissues are not imaged in the PET, which makes image segmentation,

an important preprocessing step in the registration process. A study of the segmentation

algorithms relevant to the field of medical imaging is presented. The

performance of segmentation algorithms improved with the extent of manual interaction

and intensity-based registration gave the smallest time complexity with

reasonable accuracy.