Richard A D Carano
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Explore the profile of Richard A D Carano including associated specialties, affiliations and a list of published articles.
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73
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7219
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Recent Articles
1.
Torkaman M, Jemaa S, Fredrickson J, Fernandez Coimbra A, De Crespigny A, Carano R
BMC Med Imaging
. 2025 Feb;
25(1):52.
PMID: 39962481
Background: 18-Fluoro-deoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) is a valuable imaging tool widely used in the management of cancer patients. Deep learning models excel at segmenting highly metabolic tumors but...
2.
Jemaa S, Bengtsson T, Carano R
J Clin Oncol
. 2025 Jan;
JCO2402694.
PMID: 39836943
No abstract available.
3.
Jemaa S, Ounadjela S, Wang X, El-Galaly T, Kostakoglu L, Knapp A, et al.
J Clin Oncol
. 2024 Jun;
42(25):2966-2977.
PMID: 38843483
Purpose: Artificial intelligence can reduce the time used by physicians on radiological assessments. For F-fluorodeoxyglucose-avid lymphomas, obtaining complete metabolic response (CMR) by end of treatment is prognostic. Methods: Here, we...
4.
Petrov Y, Malik B, Fredrickson J, Jemaa S, Carano R
J Digit Imaging
. 2023 Jun;
36(5):2060-2074.
PMID: 37291384
Deep neural networks (DNNs) have recently showed remarkable performance in various computer vision tasks, including classification and segmentation of medical images. Deep ensembles (an aggregated prediction of multiple DNNs) were...
5.
Krishnan A, Song Z, Clayton D, Jia X, De Crespigny A, Carano R
Sci Rep
. 2023 Mar;
13(1):4102.
PMID: 36914715
T2 lesion quantification plays a crucial role in monitoring disease progression and evaluating treatment response in multiple sclerosis (MS). We developed a 3D, multi-arm U-Net for T2 lesion segmentation, which...
6.
Ferl G, Barck K, Patil J, Jemaa S, Malamut E, Lima A, et al.
iScience
. 2022 Dec;
25(12):105712.
PMID: 36582483
Here, we have developed an automated image processing algorithm for segmenting lungs and individual lung tumors in micro-computed tomography (micro-CT) scans of mouse models of non-small cell lung cancer and...
7.
Wang X, Jemaa S, Fredrickson J, Fernandez Coimbra A, Nielsen T, De Crespigny A, et al.
BMC Med Imaging
. 2022 Mar;
22(1):58.
PMID: 35354384
Purpose: Positron emission tomography (PET)/ computed tomography (CT) has been extensively used to quantify metabolically active tumors in various oncology indications. However, FDG-PET/CT often encounters false positives in tumor detection...
8.
Song Z, Krishnan A, Gaetano L, Tustison N, Clayton D, De Crespigny A, et al.
Neuroimage Clin
. 2022 Feb;
34:102959.
PMID: 35189455
Background: Despite advancements in treatments for multiple sclerosis, insidious disease progression remains an area of unmet medical need, for which atrophy-based biomarkers may help better characterize the progressive biology. Methods:...
9.
Krishnan A, Song Z, Clayton D, Gaetano L, Jia X, De Crespigny A, et al.
Radiology
. 2021 Dec;
302(3):662-673.
PMID: 34904871
Background Deep learning-based segmentation could facilitate rapid and reproducible T1 lesion load assessments, which is crucial for disease management in multiple sclerosis (MS). T1 unenhancing and contrast-enhancing lesions in MS...
10.
Lee S, Meilandt W, Xie L, Gandham V, Ngu H, Barck K, et al.
Neuron
. 2021 Mar;
109(8):1283-1301.e6.
PMID: 33675684
Loss-of-function TREM2 mutations strongly increase Alzheimer's disease (AD) risk. Trem2 deletion has revealed protective Trem2 functions in preclinical models of β-amyloidosis, a prominent feature of pre-diagnosis AD stages. How TREM2...