# Advanced Biological Imaging for Intracellular Micromanipulation: Methods and Applications
## 3 Intracellular Micromanipulation with Computational Image Information
### Planar Localization
#### 3.1.2 Feature Reference Points  
Feature points are essential for many intracellular micromanipulation tasks as a position reference. For example, the nucleus of adherent cells is visibly ellipsoidal, and the nucleolus has explicit light intensity differences with the surroundings, so they can be localized as operation references for the manipulation of attached cells. A localization method based on K-means cluster and growing circles has been proposed [128]. In this method, circles around the nuclear region were interactively grown on the basis of the low-level information from a Canny operator. The nucleus and cytoplasm positions were identified and used as a reference for precise single cell electroporation [129], as shown in Figure 6a. In intracytoplasmic sperm injection, oocytes must be oriented properly into a desired plane to preserve the tested cells. Polar body is usually selected as the reference point to identify oocyte position. A micropipette orientation approach based on the WFFM-sampled images of a polar body has also been developed [130]. The sampled image was processed with morphological close and open operations, and a potential poly-body edge was obtained. As polar body usually looks like a bump on the cytoplasm, so the position of polar body can be recognized by calculating the average distance of potential points to the fitted center of the tested oocyte. A sheep oocyte orientation was proposed based on a holding pipette and a manipulation pipette. The polar body was out of the plane initially. The oocyte was rotated by slightly rubbing the micropipette until the polar body reached the desired position. For the period that the polar body was invisible in the current focal plane during the out-of-plane rotation, recognizing the real-time orientation from such reference points becomes relatively difficult [131]. Besides, polar body is a special intracellular organelle of oocytes, and this  
Figure 5: Segmentation of targeted specimen localization. (**a**) Trapped cell detection with a Canny edge detector and a Hough circle transform. Adapted with permission from Reference [124]; (**b**) Mitochondria localization with HSV range value. Adapted with permission from Reference [126]; (**c**) Segmentation of laser ablation region, the red circle indicates the region of interest and the trajectory shows the targeted nucleus movement. Adapted with permission from Reference [127]. method is not universal for all cell types. Therefore, polybeads were attached to the cells without polar bodies for orientation reference [132], and the three-dimensional rotation of such cells was achieved with optical tweezers. The localization of the polybead was acquired by a specific threshold pixel value, as shown in Figure 6b. However, inevitable noises and similar small particles exist around the reference polybead, so the identification of the desired point may be erroneous, and its long-term accuracy is questionable. Besides, the aforementioned visualization problem remains. Some of the inherent feature positions of cells can also be selected as reference points for orientation control [133]. Given the uniqueness of each tested cell, these feature points have to be selected individually. Super-resolution microscopy can detect small biological features with high quality. Recently, a new approach combining a STEDM with an atomic force microscope (AFM) was proposed to study the density and function of the actin cluster in mutated cells [134]. Polymerizing actin can be imaged at super-resolution by STEDM and then stimulated by an AFM tip. However, synchronization and correlation between the two systems are challenges that cannot be ignored. An automatic AFM tip detection method was proposed to record the relative position of AFM and STEDM images [135]. The area of interest was selected and then filtered to remove unnecessary details. The tip reflection was assumed to be the brightest point and identified after the iterative filter process, as shown in Figure 6c.