# SimMolCC: A Similarity of Automatically Detected Bio-Molecule Clusters between Fluorescent Cells
## 1 Introduction
One can see the fusion of synaptic vesicles, which accompanies the loss of dyes in the center and a transient increase in the surrounding fluorescence, reflecting the diffusion of dyes along the plasma membrane. Moreover, an example of observation (especially direct imaging) by TIRF microscopy of a target phenomenon, e.g., rapid tethering, of synaptic vesicles accompanying exocytosis at a fast central synapse is also shown as follows:  
[PERSON] et al. [16] applied TIRF microscopy to cerebellar mossy fiber terminals. They found that the RRP (Readily Releasable Pool) corresponds to those vesicles already resident and ready for fusion upon Ca\({}^{2+}\) influx. Following depletion of the RRP, vesicles which are within the TIRF field (100 nm) are fused in response to sustained depolarization or a train of action potentials, suggesting that newly replenished vesicles are already close to the membrane. At the same time, vesicles are recruited to the TIRF field more rapidly than they are to the calyx synapse. In addition, newly tethered vesicles can be fused with maturation times of several hundreds of milliseconds, which is much faster than that of the calyx of Held. Therefore, cerebellar mossy fiber terminals have more efficient vesicle recruitment and priming processes than those of the calyx of Held synapse. For more advances in Brain Science with more advances in ANNs and Brain Computing, in the nervous system, the following features, i.e., properties and static/dynamic behaviors, of bio-molecule clusters in many TIRF images of a fluorescent cell need to be observed and analyzed from various directions. * Properties: each bio-molecule cluster's size (e.g., the width and height of its detected Bounding Box), segmented area, shape (e.g., circle/spot-like, narrow, or odd-looking), 2D/3D position (\(x\)-, \(y\)-, and \(z\)-axes), fluorescence intensity, etc. * Static/dynamic behaviors: each bio-molecule cluster's change in state, tethering at the active zone, releasing message-carrying chemicals, vanishing from the active zone, moving in a cell, receiving and responding to message-carrying chemicals, and fusing with a membrane or with the other bio-molecule cluster(s), etc. In addition, there are various methods of analysis, as indicated: temporal analysis, spatial analysis, spatio-temporal analysis, state analysis, similarity analysis (e.g., retrieving similar cells with similar features, or clustering cells based on a similarity between cells), network/community analysis, etc. However, huge costs, e.g., a long time for manually detecting the bio-molecule clusters in many TIRF images of a fluorescent cell as well as a large sum of money for making them by TIRF microscopy, have been hindering speeding up the advancements in Brain Science, and there are other problems including biased detection and missing some of them. Therefore, as shown in Figure 1, this paper proposes a novel method for the automatic detection of the bio-molecule clusters in a TIRF image of a fluorescent cell to reduce the manual costs and solve the manual problems, and several experiments have been conducted on its performance, e.g., mAP @ IoU (mean Average Precision @ Intersection over Union) and F1-score @ IoU, as an objective/quantitative means of evaluation. The proposed method can automatically detect bio-molecule clusters that are not only circular and not always uniform in size, and it can output various histograms and heatmaps for novel deeper analyses of the automatically detected bio-molecule clusters, while the particles detected by the Mosaic Particle Tracker 2D/3D [13] can be only circular and uniform in size. In addition, this paper defines and validates a novel similarity of automatically detected bio-molecule clusters between fluorescent cells, i.e., SimMolCC, and also shows some examples of SimMolCC-based applications. The remainder of this paper is organized as follows. Section 2 introduces two kinds of related studies and compares them with this paper.