Simple Summary Lung cancer is the leading cause of malignancy-related mortality
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …

Accurate segmentation of multiple targets, such as ribs, clavicles, heart, and lung fields, from
chest X-ray images is crucial for diagnosing various lung diseases. Currently, mainstream …

Abstract Language-supervised pretraining has proven to be a valuable method for extracting
semantically meaningful features from images, serving as a foundational element in …

This paper explores the potential of using the SAM (Segment-Anything Model) segmentator
to enhance the segmentation capability of known methods. SAM is a promptable …

Humans effortlessly interpret images by parsing them into part-whole hierarchies; deep
learning excels in learning multi-level feature spaces but they often lack explicit coding of …

Recent years have experienced phenomenal growth in computer-aided diagnosis systems
based on machine learning algorithms for anomaly detection tasks in the medical image …

Human anatomy is the foundation of medical imaging and boasts one striking characteristic:
its hierarchy in nature, exhibiting two intrinsic properties:(1) locality: each anatomical …

Segmentation of clavicles and ribs in chest X-rays is significant for diagnosing lung
diseases. However, it is challenging to segment ribs because of the low contrast on chest X …

With the increasing application of large language models (LLMs) in the medical domain,
evaluating these models' performance using benchmark datasets has become crucial. This …

To identify objects in images, a complex set of skills is needed that includes understanding
the context and being able to determine the borders of objects. In computer vision, this task …