Image segmentation is a fundamental process in digital image analysis, with applications in object recognition, medical imaging, and computer vision. Traditional segmentation techniques often struggle ...

DeepGPET is a fully automatic, deep learning based method for choroid region segmentation in optical coherence tomography (OCT) scans. This algorithm can be used to segment the choroid region, and ...

This paper proposes an energy-based segmentation method facilitated by the change point detection. We apply the Kullback–Leibler (KL) divergence to demonstrate the feasibility of our method for ...

If you're sitting on a pile of customer data and wondering how to unlock hidden revenue, cross-sell analysis is your goldmine. Here’s how I approach it using Python: 1. Understand the customer base ...

The quality of radiotherapy auto-segmentation training data, primarily derived from clinician observers, is of utmost importance. However, the factors influencing the quality of clinician-derived ...

A multi-valued image (P) consisting of n-bit pixels can be decomposed into a set of n binary pictures. For example, if the image is an n-bit gray image, it is shown as, P=(P1,P2,...,Pn). In case the ...

Abstract: In this paper, we highlight image segmentation in the field of medical diagnosis, with a special emphasis on the accurate identification of retinal vessels in fundus images. Achieving ...

Cancer is a worldwide health concern and the second leading cause of death in the United States, with approximately 2 million projected cases in 2023 (1). Prostate, breast, lung, melanoma, lymphoma, ...

In clinical research on pituitary disorders, pituitary gland (PG) segmentation plays a pivotal role, which impacts the diagnosis and treatment of conditions such as endocrine dysfunctions and visual ...

Not all customers are the same. Oftentimes, different types of customers have different needs and motivations. Hence, a single approach to recruiting and retaining customers often will not yield the ...