Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor
@article{Prasanna2016CooccurrenceOL, title={Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor}, author={Prateek Prasanna and Pallavi Tiwari and Anant Madabhushi}, journal={Scientific Reports}, year={2016}, volume={6} }
In this paper, we introduce a new radiomic descriptor, Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe) for capturing subtle differences between benign and pathologic phenotypes which may be visually indistinguishable on routine anatomic imaging. CoLlAGe seeks to capture and exploit local anisotropic differences in voxel-level gradient orientations to distinguish similar appearing phenotypes. CoLlAGe involves assigning every image voxel an entropy value associated with the co…
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References
SHOWING 1-10 OF 36 REFERENCES
Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI
- Computer ScienceMICCAI
- 2014
The utility of CoLIAGe in distinguishing two subtly different types of pathologies on MRI in the context of brain tumors and breast cancer is demonstrated and CoLlAGe was found to have significantly improved classification performance, as compared to the traditional texture features.
Texture descriptors to distinguish radiation necrosis from recurrent brain tumors on multi-parametric MRI
- Computer ScienceMedical Imaging
- 2014
The utility of computer extracted texture descriptors on multi-parametric MRI (MP-MRI) to provide alternate representations of MRI that may be capable of accentuating subtle micro-architectural di erences between RN and rBT for primary and metastatic (MET) BT patients is explored.
Textural Kinetics: A Novel Dynamic Contrast-Enhanced (DCE)-MRI Feature for Breast Lesion Classification
- MedicineJournal of Digital Imaging
- 2010
Qualitatively and quantitatively demonstrated on 41 breast DCE-MRI studies that textural kinetic features outperform signal intensity kinetics and lesion morphology features in distinguishing benign from malignant lesions.
New methods of MR image intensity standardization via generalized scale
- Computer ScienceSPIE Medical Imaging
- 2005
Two new intensity standardization methods based on the concept of generalized scale were found to be better than the existing methods, with a significant improvement observed for severely diseased and abnormal patient studies.
Cell Orientation Entropy (COrE): Predicting Biochemical Recurrence from Prostate Cancer Tissue Microarrays
- Computer Science, BiologyMICCAI
- 2013
The ability of 39 COrE features to capture the characteristics of cell orientation in CaP tissue microarray (TMA) images in order to predict 10 year BCR in men with CaP following radical prostatectomy is evaluated.
Quantitative imaging in cancer evolution and ecology.
- Biology, MedicineRadiology
- 2013
Clinical imaging can enable us to define intratumoral Darwinian dynamics before and during therapy, and place clinical imaging in an increasingly central role in the development of evolution-based patient-specific cancer therapy.
Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings
- MedicineEuropean Radiology
- 2016
Preliminary analysis suggests that radiomic features from the PBZ on routine pre-operative MRI may be predictive of long- versus short-term survival in GBM, and peritumoral radiomics along with clinical factors are highly predictive of glioblastoma outcome.
Differentiating tumor recurrence from treatment necrosis: a review of neuro-oncologic imaging strategies.
- MedicineNeuro-oncology
- 2013
The possibility of computational approaches to investigate the usefulness of fine-grained imaging characteristics that are difficult to observe through visual inspection of images and a flexible treatment-planning algorithm that incorporates advanced functional imaging techniques when indicated by the patient's routine follow-up images and clinical condition are discussed.
Role of quantitative computed tomography texture analysis in the differentiation of primary lung cancer and granulomatous nodules.
- MedicineQuantitative imaging in medicine and surgery
- 2016
Quantitative CT texture analysis has the potential to differentiate primary lung cancer and granulomatous lesions.