Immunotherapy is an entirely advanced class of cancer treatment which has been highly active and exciting field in clinical therapeutics. In numerous procedures, cancer immunotherapy demands a laborious practice to recognise and count Dendritic Cells (DCs) in the vaccine preparation. Conventionally, the laser-based technology that provides a rapid analysis such as Flow Cytometry can affect the DCs viability as the staining procedure is involved. Another highly promising method which is Phase Contrast Microscopy (PCM) involves experienced pathologists to visually examine the respective microscopy images. In facts, PCM confronts complex issues regarding to imaging artifacts which can deteriorate the recognition process. As the DCs counting is crucial in cancer treatment procedures, this paper proposes a pioneering system called CasDC which implement an image processing algorithm to recognise and count DCs with a label-free method. The aim of developing this system is to establish a reliable and time saving-tool as a second reader in the clinical practice. In the meantime, the treatment procedure can be administered and therefore, improve the patient's survival rate. Our proposed system has an enormous potential towards helping Cancer Research Institute in which the system offers rapid and high throughput cancer immunotherapy vaccine preparation and automated live cell investigation. (C) 2017 The Authors. Published by Elsevier B.V.