Introduction: Escaping whole blood exhibits biochemical and physical coupled mechanisms such as coagulation and drying. However, there is no method for simultaneously monitoring the coagulation and drying procedure.Methods: In this study, a new method based on optical coherence tomography (OCT) combined with speckle variance and thickness is presented for simultaneously capturing spatially high-resolved characteristics of coagulation and drying of whole blood during the procedure. Deep learning based on a convolutional neural network (CNN) is employed for collecting OCT images with a resolution of micron order and quantitatively obtaining pixel-wise information of whole blood.Results and discussion: Then, the pixel-wise thickness map provides high-resolved temporal–spatial dynamics of whole blood during the drying procedure, and the corresponding speckle variance can uncover information of whole blood coagulation. The results demonstrate that coagulation and drying of whole blood have spatially inhomogeneous features. This method could provide the potential for revealing the coupling mechanism between coagulation and drying.