Polarization-based skin cancer detection in vivo

2021 ◽  
Author(s):  
Lioudmila Tchvialeva ◽  
Daniel C. Louie ◽  
Yuheng Wang ◽  
Sunil Kalia ◽  
Harvey Lui ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Cancer Detection ◽  
Skin Cancer Detection

scholarly journals PRELIMINARY STUDY ON SKIN CANCER DETECTION IN SENCAR MICE USING MUELLER OPTICAL COHERENCE TOMOGRAPHY

2009 ◽  
Vol 02 (03) ◽  
pp. 289-294 ◽  
Author(s):  
MILOŠ TODOROVIĆ ◽  
SHULIANG JIAO ◽  
GEORGE STOICA ◽  
LIHONG V. WANG
Keyword(s):  
Optical Coherence Tomography ◽  
Skin Cancer ◽  
Cancer Detection ◽  
Morphological Changes ◽  
Optical Coherence ◽  
Optical Scanning ◽  
Integrated Optical ◽  
Skin Cancer Detection ◽  
Continuous Source

We report on the use of a fiber-based Mueller-matrix optical coherence tomography (OCT) system with continuous source-polarization modulation for in vivo imaging of early stages of skin cancer in SENCAR mice. A homemade hand-held probe with integrated optical scanning and beam delivering optics was coupled in the sample arm. The OCT images show the morphological changes in skin resulting from pre-cancerous papilloma formations that are consistent with histology, thus demonstrating the system's potential for early skin cancer detection.

scholarly journals Parallel Classification Pipelines for Skin Cancer Detection Exploiting Hyperspectral Imaging on Hybrid Systems

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1503 ◽  
Author(s):  
Emanuele Torti ◽  
Raquel Leon ◽  
Marco La Salvia ◽  
Giordana Florimbi ◽  
Beatriz Martinez-Vega ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Hyperspectral Imaging ◽  
Cancer Detection ◽  
Medical Practice ◽  
Skin Lesions ◽  
Hyperspectral Images ◽  
Parallel Pipeline ◽  
Many Core ◽  
Skin Cancer Detection

The early detection of skin cancer is of crucial importance to plan an effective therapy to treat the lesion. In routine medical practice, the diagnosis is based on the visual inspection of the lesion and it relies on the dermatologists’ expertise. After a first examination, the dermatologist may require a biopsy to confirm if the lesion is malignant or not. This methodology suffers from false positives and negatives issues, leading to unnecessary surgical procedures. Hyperspectral imaging is gaining relevance in this medical field since it is a non-invasive and non-ionizing technique, capable of providing higher accuracy than traditional imaging methods. Therefore, the development of an automatic classification system based on hyperspectral images could improve the medical practice to distinguish pigmented skin lesions from malignant, benign, and atypical lesions. Additionally, the system can assist general practitioners in first aid care to prevent noncritical lesions from reaching dermatologists, thereby alleviating the workload of medical specialists. In this paper is presented a parallel pipeline for skin cancer detection that exploits hyperspectral imaging. The computational times of the serial processing have been reduced by adopting multicore and many-core technologies, such as OpenMP and CUDA paradigms. Different parallel approaches have been combined, leading to the development of fifteen classification pipeline versions. Experimental results using in-vivo hyperspectral images show that a hybrid parallel approach is capable of classifying an image of 50 × 50 pixels with 125 bands in less than 1 s.

scholarly journals Constructing a portable optical polarimetry probe for in-vivo skin cancer detection

2021 ◽  
Vol 26 (03) ◽  
Author(s):  
Daniel C. Louie ◽  
Lioudmila Tchvialeva ◽  
Sunil Kalia ◽  
Harvey Lui ◽  
Tim K. Lee
Keyword(s):  
Skin Cancer ◽  
Cancer Detection ◽  
Skin Cancer Detection

Deep learning enhances polarization speckle for in vivo skin cancer detection

2021 ◽  
Vol 140 ◽  
pp. 107006
Author(s):  
Yuheng Wang ◽  
Daniel C. Louie ◽  
Jiayue Cai ◽  
Lioudmila Tchvialeva ◽  
Harvey Lui ◽  
...  
Keyword(s):  
Deep Learning ◽  
Skin Cancer ◽  
Cancer Detection ◽  
Skin Cancer Detection
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