Histopathological examination of tissue sections is the gold standard for disease diagnosis. However, the conventional histopathology workflow requires lengthy and laborious sample preparation steps including tissue fixation, paraffin embedding and microtome sectioning to obtain thin tissue slices. The slices with hematoxylin and eosin (H&E) staining will be imaged under brightfield microscope to obtain histological images. The whole procedure will cause about a one-week delay to generate an accurate diagnostic report.

Microscopy with ultraviolet surface excitation (MUSE), a rapid and slide-free imaging technique, has been developed to image unprocessed fresh tissues with specific molecular contrast. The MUSE image of a typical brain biopsy (5 mm × 5 mm) with subcellular resolution can...[ Read more ]

Histopathological examination of tissue sections is the gold standard for disease diagnosis. However, the conventional histopathology workflow requires lengthy and laborious sample preparation steps including tissue fixation, paraffin embedding and microtome sectioning to obtain thin tissue slices. The slices with hematoxylin and eosin (H&E) staining will be imaged under brightfield microscope to obtain histological images. The whole procedure will cause about a one-week delay to generate an accurate diagnostic report.

Microscopy with ultraviolet surface excitation (MUSE), a rapid and slide-free imaging technique, has been developed to image unprocessed fresh tissues with specific molecular contrast. The MUSE image of a typical brain biopsy (5 mm × 5 mm) with subcellular resolution can be acquired in 5 minutes under simple procedures including hand cutting, Hoechst staining and MUSE imaging. To further assist pathologists for easy adaptation on histological image, we apply the deep learning model to translate a 5 mm × 5 mm MUSE image into a 5 mm × 5 mm Deep-MUSE image that highly resemble H&E staining in 40 seconds. The unsupervised generative adversarial network has been utilized to eliminate the need for rigidly paired data training. The workflow takes ~ 6 minutes in total to obtain a 5 mm × 5 mm Deep-MUSE image.

To demonstrate the proposed Deep-MUSE workflow, we imaged different mouse brain samples and fixed mouse liver sections. The imaging results show the quality of Deep MUSE images is comparable to the standard H&E-stained images. The novel Deep-MUSE workflow is promising to simplify the standard histopathology workflow and provide high quality histological images intraoperatively.