# Needle Segmentation in Volumetric Optical Coherence Tomography Images for Ophthalmic Microsurgery
## 1 Introduction  
Recent research shows that eye pathologies contribute to more than 280 million visual impairments [1]. Therefore, there is an increasing demand for the ophthalmic surgery due to such a large number of claims. Vitreoretinal surgery is a conventional ophthalmic operation consisting of complex manual tasks, as shown in Figure 1. The incisions, created by keratome and trocar at the sclera in a circle and 3.5 mm away from the limbus [2], are made to provide the entrance for three tools: light source, surgical tool, and irrigation cannula [3, 4]. The irrigation cannula is used for liquid injection to maintain appropriate intraocular pressure (IOP). The light source is used to illuminate the intended area on the retina, allowing the planar view of the area obtained and analyzed by surgeons through the microscope. To address these challenges, the surgical progress proposes a great challenge of delicate operation and sensitive perception to surgeons. The surgical instrument segmentation is the first step to estimate the needle pose and position, which is extremely important to enhance surgeons' concentration under low illumination intraocular condition. Among a variety of surgical tools in ophthalmic operations, the beveled needle is a widely used surgical instrument for delivering the drug into micro-structural anatomies of the eye such as retinal blood vessels and sub-retinal areas. Many studies have been carried out with significant progress in the needle segmentation through microscopic images [5; 6; 7; 8]. These works achieved satisfactory results using either color-based or geometry-based features. Nevertheless, due to the limitation of two-dimensional (2D) microscopic images, these detection results in en-face plane view cannot provide enough information to locate the needle pose and position in three-dimensional (3D) space. Many widely used 3D medical imaging technologies, such as computed tomography (CT) scans, fluoroscopy, magnetic resonance (MR) and ultrasound are already applied in brain, thoracic and cardiac surgeries, not only for diagnostic procedures but also as real-time surgical guides [9; 10; 11; 12; 13]. However, these imaging modalities cannot achieve a sufficient resolution for ophthalmic interventions. For instance, in MRI-guided interventions with millimeter resolution in breast and prostate biopsies, 18 gauge needles with a diameter of 1.27 mm are used. Yet for ophthalmic surgery, 30 gauge needles with a diameter of 0.31 mm require resolution submillimeter [14]. Optical Coherence Tomography (OCT) is originally used in ophthalmic diagnosis for its micron level resolution [15]. Recently, OCT application has been extented to provide real-time information of intra-operative interactions between the surgical instrument and intraocular tissue [16]. The microscope-mounted intra-operative OCT (iOCT) developed by Carl Zeiss Meditec (RESCAN 700) was firstly described in clinical use in 2014 [17]. The iOCT integrated to on this microscope is capable of sharing the same optical path with the microscopic view and provide real-time cross section information, which is an ideal imaging modality for ophthalmic surgeries. The iOCT device can also obtain a volumetric image cubes with multi B-scans acquirements. The scan area can be adjusted via region-of-interest (ROI) shown in the microscopic images in CALLISTO eye assistance computer system. When using iOCT to estimate the needle pose and position, the first step is to obtain the needle point cloud and to segment the needle voxels in the volumetric OCT images. Apart from the difficulties caused by image speckle, low contrast, signal loss due to shadowing, and refraction artifacts, the needle in OCT images has much more details of the tip part (needle may have several fragments in the B-scan image) and has illusory needle reflection [18]. All these challenges make needle segmentation in OCT images different from other imaging modalities such as 3D ultrasound.