Detalhe da pesquisa
1.
Nondestructive 3D pathology with analysis of nuclear features for prostate cancer risk assessment.
J Pathol
; 260(4): 390-401, 2023 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-37232213
2.
Visual Assessment of 2-Dimensional Levels Within 3-Dimensional Pathology Data Sets of Prostate Needle Biopsies Reveals Substantial Spatial Heterogeneity.
Lab Invest
; 103(12): 100265, 2023 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-37858679
3.
Intra-nucleus mosaic pattern (InMop) and whole-cell Haralick combined-descriptor for identifying and characterizing acute leukemia blasts on single cell peripheral blood images.
Cytometry A
; 103(11): 857-867, 2023 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-37565838
4.
The state of the art for artificial intelligence in lung digital pathology.
J Pathol
; 257(4): 413-429, 2022 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-35579955
5.
Computer-extracted features of nuclear morphology in hematoxylin and eosin images distinguish stage II and IV colon tumors.
J Pathol
; 257(1): 17-28, 2022 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-35007352
6.
Image analysis reveals differences in tumor multinucleations in Black and White patients with human papillomavirus-associated oropharyngeal squamous cell carcinoma.
Cancer
; 128(21): 3831-3842, 2022 11 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-36066461
7.
Oropharyngeal cancer outcomes correlate with p16 status, multinucleation and immune infiltration.
Mod Pathol
; 35(8): 1045-1054, 2022 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-35184149
8.
Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies.
J Pathol
; 253(3): 268-278, 2021 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-33197281
9.
An automated computational image analysis pipeline for histological grading of cardiac allograft rejection.
Eur Heart J
; 42(24): 2356-2369, 2021 06 21.
Artigo
em Inglês
| MEDLINE | ID: mdl-33982079
10.
Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains.
Kidney Int
; 99(1): 86-101, 2021 01.
Artigo
em Inglês
| MEDLINE | ID: mdl-32835732
11.
Quality control stress test for deep learning-based diagnostic model in digital pathology.
Mod Pathol
; 34(12): 2098-2108, 2021 12.
Artigo
em Inglês
| MEDLINE | ID: mdl-34168282
12.
Prospective Evaluation of Repeatability and Robustness of Radiomic Descriptors in Healthy Brain Tissue Regions In Vivo Across Systematic Variations in T2-Weighted Magnetic Resonance Imaging Acquisition Parameters.
J Magn Reson Imaging
; 54(3): 1009-1021, 2021 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-33860966
13.
Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps.
Eur Radiol
; 31(1): 379-391, 2021 Jan.
Artigo
em Inglês
| MEDLINE | ID: mdl-32700021
14.
T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning-derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology.
Eur Radiol
; 31(3): 1336-1346, 2021 Mar.
Artigo
em Inglês
| MEDLINE | ID: mdl-32876839
15.
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises.
Proc IEEE Inst Electr Electron Eng
; 109(5): 820-838, 2021 May.
Artigo
em Inglês
| MEDLINE | ID: mdl-37786449
16.
A new machine learning approach for predicting likelihood of recurrence following ablation for atrial fibrillation from CT.
BMC Med Imaging
; 21(1): 45, 2021 03 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-33750343
17.
Repeatability of radiomics and machine learning for DWI: Short-term repeatability study of 112 patients with prostate cancer.
Magn Reson Med
; 83(6): 2293-2309, 2020 06.
Artigo
em Inglês
| MEDLINE | ID: mdl-31703155
18.
Radiomic Features of Primary Rectal Cancers on Baseline T2 -Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study.
J Magn Reson Imaging
; 52(5): 1531-1541, 2020 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-32216127
19.
Quantitative nuclear histomorphometric features are predictive of Oncotype DX risk categories in ductal carcinoma in situ: preliminary findings.
Breast Cancer Res
; 21(1): 114, 2019 10 17.
Artigo
em Inglês
| MEDLINE | ID: mdl-31623652
20.
Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas.
Radiology
; 290(3): 783-792, 2019 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-30561278