Abstract
This study introduces a comprehensive hardware-software framework designed to enhance the quality of block face image capture-an essential intermediary step for registering 2D histology images to ex vivo magnetic resonance (MR) images. A customized camera mounting and lighting system is employed to maintain consistent relative positioning and lighting conditions. Departing from traditional transparent paraffin, dyed paraffin is utilized to enhance contrast for subsequent automatic segmentation. Our software facilitates fully automated data collection and organization, complemented by a real-time Quality Assurance (QA) section to assess the captured image's quality during the sectioning process. The setup is evaluated and validated using rabbit muscle and rat brain which underwent MR-guided focused ultrasound ablations. The customized hardware system establishes a robust image capturing environment. The software with a real-time QA section, enables operators to promptly rectify low-quality captures, thereby preventing data loss. The execution of our proposed framework produces robust registration results for H&E images to ex vivo MR images.•The presented hardware-software framework ensures the uniformity and resilience of the block face image capture process, contributing to a more reliable and efficient registration of 2D histology images to ex vivo MR images.