OpenSRH: optimizing brain tumor surgery using intraoperative stimulated Raman histology

by   Cheng Jiang, et al.

Accurate intraoperative diagnosis is essential for providing safe and effective care during brain tumor surgery. Our standard-of-care diagnostic methods are time, resource, and labor intensive, which restricts access to optimal surgical treatments. To address these limitations, we propose an alternative workflow that combines stimulated Raman histology (SRH), a rapid optical imaging method, with deep learning-based automated interpretation of SRH images for intraoperative brain tumor diagnosis and real-time surgical decision support. Here, we present OpenSRH, the first public dataset of clinical SRH images from 300+ brain tumors patients and 1300+ unique whole slide optical images. OpenSRH contains data from the most common brain tumors diagnoses, full pathologic annotations, whole slide tumor segmentations, raw and processed optical imaging data for end-to-end model development and validation. We provide a framework for patch-based whole slide SRH classification and inference using weak (i.e. patient-level) diagnostic labels. Finally, we benchmark two computer vision tasks: multiclass histologic brain tumor classification and patch-based contrastive representation learning. We hope OpenSRH will facilitate the clinical translation of rapid optical imaging and real-time ML-based surgical decision support in order to improve the access, safety, and efficacy of cancer surgery in the era of precision medicine. Dataset access, code, and benchmarks are available at


page 2

page 5

page 15

page 18

page 20

page 21

page 22


Contrastive Representation Learning for Rapid Intraoperative Diagnosis of Skull Base Tumors Imaged Using Stimulated Raman Histology

Background: Accurate diagnosis of skull base tumors is essential for pro...

Intra-operative Brain Tumor Detection with Deep Learning-Optimized Hyperspectral Imaging

Surgery for gliomas (intrinsic brain tumors), especially when low-grade,...

Artificial-intelligence-based molecular classification of diffuse gliomas using rapid, label-free optical imaging

Molecular classification has transformed the management of brain tumors ...

Dense Error Map Estimation for MRI-Ultrasound Registration in Brain Tumor Surgery Using Swin UNETR

Early surgical treatment of brain tumors is crucial in reducing patient ...

Please sign up or login with your details

Forgot password? Click here to reset