Marc J. Pomeroy

Medical Imaging 2.0: A New Look at Physical Measurements from Dynamic Biological Systems of in vivo Tissues for Early Cancer Detection

Junfeng Liang, Ryan Kuo, Marc J. Pomeroy, Su-Youne Chang et autres

Expert interpretation of medical images for lesion diagnosis may not always align with the underlying in vivo tissue pathology and thus cannot be considered a definitive truth for malignancy or benignity. This discrepancy poses a major barrier to effective low dose computed …

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Leveraging prior knowledge in machine intelligence to improve lesion diagnosis for early cancer detection

Zhengrong Jerome Liang, Shaojie Chang, Yongfeng Gao, Weiguo Cao et autres

BACKGROUND: Experts' interpretations of medical images for lesion diagnosis may not always align with the underlying in vivo tissue pathology and, therefore, cannot be considered the definitive truth regarding malignancy or benignity. While current machine learning (ML) models in medical imaging can …

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Leveraging prior knowledge in machine intelligence for improving cancer diagnostic accuracy

Zhengrong Liang, Shaojie Chang, Yongfeng Gao, Weiguo Cao et autres

Understanding the Morphological Development of Oxidation Products Formed on β-sialon Materials with Different z-values

Marc J. Pomeroy, R. Ramesh

The oxidation behaviour of β-sialons (Si( 6-z )Al z O z N( 8-z ) with z-values of 0.2, 0.5, 1.0, 1.5, 2.0 and 3.0 at 1350°C is reported for times up to 256 h. The sialons can be grouped into two categories …

An Expert-Driven Machine Learning for Medical Imaging-Based Diagnosis of Lesions

Zeming Liang, Licheng R. Kuo, Marc J. Pomeroy, Su-Youne Chang et autres

This paper describes an expert-driven, instead of data-driven, machine learning (EdML) to characterize in vivo tissues for medical imaging-based diagnosis of lesions. The presented EdML mimics experts’ performance by incorporating experts’ prior knowledge into analysis of data to accomplish a task that …

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Lesion Classification by Model-Based Feature Extraction: A Differential Affine Invariant Model of Soft Tissue Elasticity in CT Images

Weiguo Cao, Marc J. Pomeroy, Zhengrong Liang, Yongfeng Gao et autres

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Comparison of Extracting Tissue- and Image-based Characteristic Features for Machine Learning Prediction of Colorectal Polyp Malignancy

L Kuo, Marc J. Pomeroy, Yongfeng Gao, Weiguo Cao et autres

Detection and classification of precursor polyp via computed tomography colonography (CTC) has shown its significant clinical impact on management of colorectal cancer (CRC). In this study, we compared the classification performance of five machine learning (ML) models and one deep learning (DL) …

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Diffusion braze homogenisation and contraction during re-repair heat treatments of a single crystal nickel-based superalloy

Eoin P. Hinchy, D. D. Barron, Marc J. Pomeroy, David A. Tanner

In this work, nickel-based braze reservoirs embedded in single crystal nickel-based superalloy substrates were cycled between one and four braze diffusion heat treatments to analyse the effect on microstructural transformation of the braze and substrate materials. Nickel-based superalloy turbine components can undergo …

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Effect of fluorine and nitrogen content on the properties of Ca-Mg-Si-Al-O-(N)-(F) glasses

Ángel R. García‐Bellés, Carolina Clausell-Terol, A. Barba, Marc J. Pomeroy et autres

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The effect of single crystal and welded substrates on the development of braze microstructures

Eoin P. Hinchy, Marc J. Pomeroy, David A. Tanner

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Bioactivity potential of calcium alumino-silicate glasses and glass–ceramics containing nitrogen and fluorine

Amir Reza Hanifi, Clare M. Crowley, Marc J. Pomeroy, Stuart Hampshire

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Properties of Ca –( Y )– Si – Al – O – N – F Glasses: Independent and Additive Effects of Fluorine and Nitrogen

Ángel R. García‐Bellés, María Monzó, A. Barba, Carolina Clausell-Terol et autres

Thirty glasses of composition (in equivalent percent) 20‐xCa:xY:50Si:30Al:(100‐y‐z)O:yN:zF, with x = 0, 10; y = 0, 10, 20, and z = 0, 1, 3, 5, 7 were prepared by melting and casting. All glasses were X‐ray amorphous. Glass molar volumes ( MV …

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