3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstruction
| العنوان: | 3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstruction |
|---|---|
| المؤلفون: | Christian A. Kunder, Anugayathri Jawahar, Wei Shao, Richard E. Fan, Simon John Christoph Soerensen, Pejman Ghanouni, Jeffrey B. Wang, Rewa Sood, Nikola C. Teslovich, Mirabela Rusu, Nikhil Madhuripan, Geoffrey A. Sonn, James D. Brooks |
| المصدر: | Sood, R R, Shao, W, Kunder, C, Teslovich, N C, Wang, J B, Soerensen, S J C, Madhuripan, N, Jawahar, A, Brooks, J D, Ghanouni, P, Fan, R E, Sonn, G A & Rusu, M 2021, ' 3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstruction ', Medical Image Analysis, vol. 69, 101957 . https://doi.org/10.1016/j.media.2021.101957 Med Image Anal |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Male, medicine.medical_specialty, Generative adversarial networks, Computer science, HISTOLOGICAL SECTIONS, medicine.medical_treatment, Health Informatics, images onto MRI, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Prostate, medicine, Humans, Radiology, Nuclear Medicine and imaging, Volume reconstruction, Projection (set theory), nbsp, 3d registration, Radiological and Ultrasound Technology, Prostatectomy, Mapping cancer from histopathology&, Prostatic Neoplasms, Super-resolution registration, Magnetic Resonance Imaging, Computer Graphics and Computer-Aided Design, Superresolution, Mapping cancer from histopathology images onto MRI, medicine.anatomical_structure, Radiology pathology fusion, Histopathology, Computer Vision and Pattern Recognition, Radiology, 030217 neurology & neurosurgery, Interpolation |
| الوصف: | The use of MRI for prostate cancer diagnosis and treatment is increasing rapidly. However, identifying the presence and extent of cancer on MRI remains challenging, leading to high variability in detection even among expert radiologists. Improvement in cancer detection on MRI is essential to reducing this variability and maximizing the clinical utility of MRI. To date, such improvement has been limited by the lack of accurately labeled MRI datasets. Data from patients who underwent radical prostatectomy enables the spatial alignment of digitized histopathology images of the resected prostate with corresponding pre-surgical MRI. This alignment facilitates the delineation of detailed cancer labels on MRI via the projection of cancer from histopathology images onto MRI. We introduce a framework that performs 3D registration of whole-mount histopathology images to pre-surgical MRI in three steps. First, we developed a novel multi-image super-resolution generative adversarial network (miSRGAN), which learns information useful for 3D registration by producing a reconstructed 3D MRI. Second, we trained the network to learn information between histopathology slices to facilitate the application of 3D registration methods. Third, we registered the reconstructed 3D histopathology volumes to the reconstructed 3D MRI, mapping the extent of cancer from histopathology images onto MRI without the need for slice-to-slice correspondence. When compared to interpolation methods, our super-resolution reconstruction resulted in the highest PSNR relative to clinical 3D MRI (32.15 dB vs 30.16 dB for BSpline interpolation). Moreover, the registration of 3D volumes reconstructed via super-resolution for both MRI and histopathology images showed the best alignment of cancer regions when compared to (1) the state-of-the-art RAPSODI approach, (2) volumes that were not reconstructed, or (3) volumes that were reconstructed using nearest neighbor, linear, or BSpline interpolations. The improved 3D alignment of histopathology images and MRI facilitates the projection of accurate cancer labels on MRI, allowing for the development of improved MRI interpretation schemes and machine learning models to automatically detect cancer on MRI. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::50c36cdf7003c0f048d0f5523d42e875 https://pure.au.dk/portal/da/publications/3d-registration-of-presurgical-prostate-mri-and-histopathology-images-via-superresolution-volume-reconstruction(55572bc8-c0b3-4aa4-bf13-bd0322eec5f4).html |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....50c36cdf7003c0f048d0f5523d42e875 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |