Melanoma of the Skin

Compton, Carolyn C.; Byrd, David R.; Garcia‐Aguilar, Julio; Kurtzman, Scott H.; Olawaiye, Alexander; Washington, Mary Kay

doi:10.1007/978-1-4614-2080-4_31

Cited by 8 publications

(1 citation statement)

References 108 publications

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“…Inverse procedures that are useful for estimating thermophysical parameters and growth features of skin lesions are gaining more and more interest due to the increasing development of IR cameras and computational capacity. Indeed, information regarding the thermal properties of a lesion leads to more reliable numerical models, and on the other hand, an accurate estimate of the lesion penetration depth provides relevant information about the tumor stage to which it is related [67], reducing the cases of unnecessary biopsies required for stage characterization.…”

Section: Inverse Modelingmentioning

confidence: 99%

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

D’Alessandro,

Tavakolian,

Sfarra

2024

Applied Sciences

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The present review aims to analyze the application of infrared thermal imaging, aided by bio-heat models, as a tool for the diagnosis of skin and breast cancers. The state of the art of the related technical procedures, bio-heat transfer modeling, and thermogram post-processing methods is comprehensively reviewed. Once the thermal signatures of different malignant diseases are described, the updated thermographic techniques (steady-state and dynamic) used for cancer diagnosis are discussed in detail, along with the recommended best practices to ensure the most significant thermal contrast observable between the cancerous and healthy tissues. Regarding the dynamic techniques, particular emphasis is placed on innovative methods, such as lock-in thermography, thermal wave imaging, and rotational breast thermography. Forward and inverse modeling techniques for the bio-heat transfer in skin and breast tissues, supporting the thermographic examination and providing accurate data for training artificial intelligence (AI) algorithms, are reported with a special focus on real breast geometry-based 3D models. In terms of inverse techniques, different data processing algorithms to retrieve thermophysical parameters and growth features of tumor lesions are mentioned. Post-processing of infrared images is also described, citing both conventional processing procedures and applications of AI algorithms for tumor detection.

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Section: Inverse Modelingmentioning

confidence: 99%

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

D’Alessandro,

Tavakolian,

Sfarra

2024

Applied Sciences

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Association of Advanced Leukemic Stage and Skin Cancer Tumor Stage With Poor Skin Cancer Outcomes in Patients With Chronic Lymphocytic Leukemia

et al. 2014

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In patients with CLL and non-basal cell carcinoma skin cancer, mortality is as high from skin cancer as from CLL. The Rai stage and skin cancer T stage should be considered when risk-stratifying patients with skin cancer. Regular communication between dermatologists and oncologists will help facilitate the identification of patients with CLL who are at high risk of having poor skin cancer outcomes.

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Melanoma

Shaw

Grobmyer

2014

Surgical Oncology

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Melanoma of the Skin

Cited by 8 publications

References 108 publications

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

Association of Advanced Leukemic Stage and Skin Cancer Tumor Stage With Poor Skin Cancer Outcomes in Patients With Chronic Lymphocytic Leukemia

Melanoma

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