# Accurate Needle Localization in the Image Frames of Ultrasound Videos
## 1 Introduction  
Accurate needle insertion is essential in numerous medical interventions, including biopsy, brachytherapy, and needle-based nerve blocks. These interventions rely on accurateneedle placement to achieve successful outcomes and prevent damage to surrounding tissues [1; 2]. Ultrasound imaging is used in many healthcare systems for guiding needle insertion due to its ability to provide real-time two-dimensional (2D) videos of the advancing needle and the surrounding tissues [1; 3; 4; 5; 6; 7]. The widespread adoption of ultrasound guidance for needle interventions can be attributed to its safety, portability, and cost-effectiveness. Despite the widespread use of ultrasound guidance for needle interventions, detecting the needle in 2D ultrasound videos remains a challenging task. The needle often appears in ultrasound videos as a bright, linear structure, but other anatomical features, such as fat interfaces and bones, can produce similar high-intensity linear reflections. Additionally, acoustic artifacts, including shadowing and attenuation, can degrade the needle visibility [8]. Aligning the ultrasound imaging plane to accurately visualize the target anatomy and the needle presents another challenge. Several techniques were introduced to identify the needle in ultrasound images and videos. The reader is referred to the studies by [PERSON] et al. [9] and [PERSON] et al. [10] for a detailed review of these methods. In general, these methods can be grouped into three main approaches: external needle tracking systems, customized ultrasound excitations to enhance needle visibility, and ultrasound image analysis to identify the needle. The approach of utilizing a tracking system to track the needle has been employed in many previous studies. For example, [PERSON] et al. [11] employed two stereo cameras mounted on the ultrasound probe to track the needle in ultrasound images. [PERSON] et al. [12] utilized a single camera mounted on the ultrasound transducer to estimate the needle axis based on a mathematical formulation that considers the known spacing between the markings found on some clinical needles. [PERSON] et al. [13] proposed a combined algorithm that integrates a camera-based estimation of the needle axis with ultrasound image analysis to achieve precise prediction of the needle in three-dimensional ultrasound volumes. In addition to cameras, several studies proposed alternative tracking systems for needle detection. For example, [PERSON] et al. [14] used an electromagnetic tracker to identify the needle. [PERSON] et al. [15] utilized an optical navigation system to localize the needle. Nevertheless, external tracking systems for needle detection often present limitations [1]. For example, electromagnetic trackers are sensitive to interference from nearby metallic objects, while optical trackers require a clear line of sight. Many studies utilized customized ultrasound imaging excitations to improve needle visibility. For instance, [PERSON] and [PERSON] [16] developed an adaptive ultrasound beam-steering method to enhance needle visibility in linear ultrasound scans. This method continuously adjusts the ultrasound beam direction to remain orthogonal to the needle, thereby maximizing the echoes received from the needle. [PERSON] et al. [17] integrated the adaptive beam steering method with a machine learning-based algorithm to segment the needle. [PERSON] et al. [18] proposed a signature-based approach for detecting the needle based on ultrasound radio-frequency signals. The approach processes the radio-frequency signals using signature-based analysis to recognize needle echoes. The recognized needle echoes are then analyzed to predict the needle's location in the ultrasound image. Furthermore, several research studies [19; 20; 21; 22] suggested the utilization of a stimulator to activate the needle, followed by Doppler ultrasound imaging to identify the vibrations produced by the stimulated needle. The ultrasound image analysis approach is widely used to detect the needle. For example, [PERSON] et al.