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Explainable AI for CNN-based prostate tumor segmentation in multi-parametric MRI correlated to whole mount histopathology
2022
Radiation Oncology
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The CNN uses a U-Net architecture which was trained on multi-parametric MRI data from 122 patients to automatically segment the prostate gland and prostate tumor lesions. ...
The CNN achieved a mean Dice Sorensen Coefficient 0.62 and 0.31 for the prostate gland and the tumor lesions -with the radiologist drawn ground truth and 0.32 with whole-mount histology ground truth for ...
., Novi, MI, United States) in creation of new software and data processing techniques used in major parts of this work is gratefully acknowledged. ...
doi:10.1186/s13014-022-02035-0
pmid:35366918
pmcid:PMC8976981
fatcat:gfjy2z7r7bfvxd45pwedzj7fii
Machine learning applications in prostate cancer magnetic resonance imaging
2019
European Radiology Experimental
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With this review, we aimed to provide a synopsis of recently proposed applications of machine learning (ML) in radiology focusing on prostate magnetic resonance imaging (MRI). ...
The following potential clinical applications in different settings are outlined, many of them based only on MRI-unenhanced sequences: gland segmentation; assessment of lesion aggressiveness to distinguish ...
[54] trained a ML algorithm with paired CT and MRI datasets in order to generate synthetic CT images to be used for patient radiation therapy setup and dose calculation. ...
doi:10.1186/s41747-019-0109-2
pmid:31392526
pmcid:PMC6686027
fatcat:7x3egaxnjzcdpngl5vogww27gi
Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI
2014
Medical Imaging 2014: Image Processing
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Nine pairs of synthetic T1-weighted to T2-weighted brain MRI were registered under the following conditions: five levels of noise (0%, 1%, 3%, 5%, and 7%) and two levels of bias field (20% and 40%) each ...
We also spatially align twenty-six ex vivo histology sections and in vivo prostate MRI in order to map the spatial extent of prostate cancer onto corresponding radiologic imaging. ...
Summary of experimental protocol for synthetic T1-w and T2-w BrainWeb and clinical prostate histology and MRI data. ...
doi:10.1117/12.2044317
dblp:conf/miip/HwuangRKASSTRFM14
fatcat:4saaiovoyfgrddhfuq7vkcovoa
Computer-aided diagnosis: detection and localization of prostate cancer within the peripheral zone
2015
International Journal for Numerical Methods in Biomedical Engineering
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We are focusing on developing a CAD tool for the detection and localisation of abnormal region within the PZ in T2-MRI imaging. ...
Secondly, the development of the proposed method and its application in prostate cancer detection and localisation using a single MRI modality with the results comparable to the state-of-the-art multi-modality ...
This work was funded in part by the NISCHR Biomedical Research Unit for Advanced Medical Imaging and Visualization. ...
doi:10.1002/cnm.2745
pmid:26313267
fatcat:wavimncnhjba5lzyw2qxdjcxmm
Elastic registration of multimodal prostate MRI and histology via multiattribute combined mutual information
2011
Medical Physics (Lancaster)
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Results: Elastic registration using the multivariate MI formulation is demonstrated for 150 corresponding sets of prostate images from 25 patient studies with T2-weighted and dynamic-contrast enhanced ...
Purpose: By performing registration of preoperative multiprotocol in vivo magnetic resonance ͑MR͒ images of the prostate with corresponding whole-mount histology ͑WMH͒ sections from postoperative radical ...
T2-w MRI, for the synthetic data set. ...
doi:10.1118/1.3560879
pmid:21626933
pmcid:PMC3078156
fatcat:5xk7kmfge5d7fobjrl462yryfy
Multimodal Self-Supervised Learning for Medical Image Analysis
[article]
2020
arXiv
pre-print
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In other words, we exploit synthetic images for self-supervised pretraining, instead of downstream tasks directly, in order to circumvent quality issues associated with synthetic images, while improving ...
We showcase our approach on four downstream tasks: Brain tumor segmentation and survival days prediction using four MRI modalities, Prostate segmentation using two MRI modalities, and Liver segmentation ...
In the BraTS and Prostate benchmarks, we use T2-weighted MRI. In the Prostate dataset, we use T2-weighted MRI scans to generate the ADC diffusion-weighted scans. ...
arXiv:1912.05396v2
fatcat:klwchysg4ney3phlmlawyrzxvi
Machine Learning in Prostate MRI for Prostate Cancer: Current Status and Future Opportunities
2022
Diagnostics
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The Prostate Imaging Reporting and Data System (PI-RADS) is an established imaging-based scoring system that scores the probability of clinically significant prostate cancer on MRI to guide management. ...
Advances in our understanding of the role of magnetic resonance imaging (MRI) for the detection of prostate cancer have enabled its integration into clinical routines in the past two decades. ...
For prostate zones, WG = whole gland, PZ = peripheral zone, TZ = transition zone. ...
doi:10.3390/diagnostics12020289
pmid:35204380
pmcid:PMC8870978
fatcat:rpaecwqodveqplmvuyvu5ne52m
Normal and Variant Pelvic Anatomy on MRI
2011
Magnetic Resonance Imaging Clinics of North America
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Sagittal T2-weighted image demonstrates anterior linear defect in the lower uterine segment (arrow) compatible with cesarean section scar. ...
Finally, whole-pelvis imaging is performed using a wide FOV in conjunction with the surface coil. ...
doi:10.1016/j.mric.2011.05.001
pmid:21816330
fatcat:4y5fso5bzfezflwg7dflgleeom
Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives
2021
Diagnostics
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Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. ...
When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. ...
Quantitative results showed no significant differences in dose volume histogram and planning target volumes, showing that in the future ML-MRI methods could generate synthetic CT images from MRI and could ...
doi:10.3390/diagnostics11020354
pmid:33672608
pmcid:PMC7924061
fatcat:jqktyzjrhjh2jaxvlpk3pomube
Learning Non-rigid Deformations for Robust, Constrained Point-based Registration in Image-Guided MR-TRUS Prostate Intervention
2017
Medical Image Analysis
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State-of-the-art, clinical MR-TRUS image fusion relies upon semi-automated segmentations of the prostate in both the MR and the TRUS images to perform non-rigid surface-based registration of the gland. ...
Segmentation of the prostate in TRUS imaging is itself a challenging task and prone to high variability. ...
Validation Using Synthetic Data We leveraged our large database to generate a set of realistic, synthetic TRUS prostate shapes with known non-rigid deformations and known segmentation errors on which we ...
doi:10.1016/j.media.2017.04.001
pmid:28431275
pmcid:PMC5514316
fatcat:x6zntiw2gfgg5hk5zmuoy5t6k4
Registration of pre-surgical MRI and whole-mount histopathology images in prostate cancer patients with radical prostatectomy via RAPSODI
[article]
2019
arXiv
pre-print
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543 histopathology slices that were registered to corresponding T2 weighted MRI slices. ...
Magnetic resonance imaging (MRI) has great potential to improve prostate cancer diagnosis. ...
All summarized methods require as input the in vivo pre-surgical T2 weighted MRI, digitized serial histopathology images, and the segmentation of the prostate on MRI and histopathology images; Additional ...
arXiv:1907.00324v2
fatcat:636ftyvq7zf25k2yfnwgrdqp64
Front Matter: Volume 12032
2022
Medical Imaging 2022: Image Processing
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These two-number sets start with 00, ...
diffusion-weighted data using tagged magnetic resonance imaging [
models for organ contouring in head and neck radiotherapy [12032-13] 0G Automatic classification of MRI contrasts using a deep siamese ...
inference for quantifying inter-observer variability in segmentation of anatomical structures [12032-55] 1N Parotid gland segmentation with nnU-Net: deployment scenario and inter-observer variability ...
doi:10.1117/12.2638192
fatcat:ikfgnjefaba2tpiamxoftyi6sa
Multiparametric MRI for Prostate Cancer Characterization: Combined Use of Radiomics Model with PI-RADS and Clinical Parameters
2020
Cancers
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Segmentations of the whole prostate glands and index lesions were performed manually in apparent diffusion coefficient (ADC) maps and T2-weighted MRI. ...
Radiomic features were extracted from regions corresponding to the whole prostate gland and index lesion. ...
Image Segmentations For each patient, the whole prostate gland, peripheral and transition zones, as well as index lesions of the prostate were manually segmented on T2-weighted images. ...
doi:10.3390/cancers12071767
pmid:32630787
fatcat:pbd4aj6wljf6nh4gd4r2g6go4u
Molecular imaging and fusion targeted biopsy of the prostate
2016
Clinical and translational imaging
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Results-Molecular imaging with PET and MRI shows promising results in the early detection of prostate cancer. ...
Purpose-This paper provides a review on molecular imaging with positron emission tomography (PET) and magnetic resonance imaging (MRI) for prostate cancer detection and its applications in fusion targeted ...
Fig. 1 .Fig. 2 . 12 Multiparametric MRI of the prostate: T2-weighted MRI (left), DCE-MRI (middle), and diffusion-weighted MRI (right) of the same Imaging. ...
doi:10.1007/s40336-016-0214-7
pmid:28971090
pmcid:PMC5621648
fatcat:zogw3brx5bd3lerltvgxbaqjna
18F-Choline PET/MRI: The Additional Value of PET for MRI-Guided Transrectal Prostate Biopsies
2016
Journal of Nuclear Medicine
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The biopsy procedure was performed after registration of real-time transrectal ultrasound with T2-weighted MR and included imageguided cores plus standard cores. ...
Methods: Within an ongoing prospective clinical trial, hybrid 18 F-choline PET/CT and multiparametric 3T MRI (mpMRI) of the pelvis were performed in 36 subjects with a rising prostate-specific antigen ...
In vivo MRI pelvis examinations of the prostate gland with and without contrast material was performed before biopsy. ...
doi:10.2967/jnumed.115.170878
pmid:26985061
pmcid:PMC5819614
fatcat:prhv3msbgvbz5b642alob2ueau
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