Multimodal digital color imaging system for facial skin lesion analysis

2008 ◽  
Author(s):  
Youngwoo Bae ◽  
Youn-Heum Lee ◽  
Byungjo Jung
Keyword(s):  
Skin Lesion ◽  
Imaging System ◽  
Facial Skin ◽  
Color Imaging ◽  
Lesion Analysis ◽  
Digital Color Imaging

Digital Color Imaging Handbook

2004 ◽  
Vol 29 (5) ◽  
pp. 395-397 ◽  
Author(s):  
Joann Taylor
Keyword(s):  
Color Imaging ◽  
Digital Color Imaging

scholarly journals Improving Skin Lesion Analysis with Generative Adversarial Networks

2020 ◽  
Author(s):  
Alceu Bissoto ◽  
Sandra Avila
Keyword(s):  
Skin Lesion ◽  
State Of The Art ◽  
Synthetic Data ◽  
Clinical Information ◽  
Analysis Data ◽  
Training Dataset ◽  
Generative Adversarial Networks ◽  
Classification Models ◽  
Adversarial Networks ◽  
Lesion Analysis

Melanoma is the most lethal type of skin cancer. Early diagnosis is crucial to increase the survival rate of those patients due to the possibility of metastasis. Automated skin lesion analysis can play an essential role by reaching people that do not have access to a specialist. However, since deep learning became the state-of-the-art for skin lesion analysis, data became a decisive factor in pushing the solutions further. The core objective of this M.Sc. dissertation is to tackle the problems that arise by having limited datasets. In the first part, we use generative adversarial networks to generate synthetic data to augment our classification model’s training datasets to boost performance. Our method generates high-resolution clinically-meaningful skin lesion images, that when compound our classification model’s training dataset, consistently improved the performance in different scenarios, for distinct datasets. We also investigate how our classification models perceived the synthetic samples and how they can aid the model’s generalization. Finally, we investigate a problem that usually arises by having few, relatively small datasets that are thoroughly re-used in the literature: bias. For this, we designed experiments to study how our models’ use data, verifying how it exploits correct (based on medical algorithms), and spurious (based on artifacts introduced during image acquisition) correlations. Disturbingly, even in the absence of any clinical information regarding the lesion being diagnosed, our classification models presented much better performance than chance (even competing with specialists benchmarks), highly suggesting inflated performances.

scholarly journals A Dual-Color Imaging System for Sugarcane Smut Fungus Sporisorium scitamineum

Plant Disease ◽  
2016 ◽  
Vol 100 (12) ◽  
pp. 2357-2362 ◽  
Author(s):  
Meixin Yan ◽  
Enping Cai ◽  
Jianuan Zhou ◽  
Changqing Chang ◽  
Pinggen Xi ◽  
...  
Keyword(s):  
Life Cycle ◽  
Fluorescent Protein ◽  
Imaging System ◽  
Abiotic Factors ◽  
Smut Fungus ◽  
Color Imaging ◽  
Sporisorium Scitamineum ◽  
Dual Color ◽  
Life Cycle Development ◽  
Whole Life Cycle

The life cycle of the sugarcane smut fungus Sporisorium scitamineum is a multistep process. Haploid sporidia of compatible (MAT-1 versus MAT-2) mating types fuse to generate pathogenic dikaryotic hyphae to infect the host. Within the host tissues, diploid teliospores are formed and induce a characteristic sorus that looks like a black whip. The diploid teliospores germinate to form haploid sporidia by meiosis. In order to monitor fungal development throughout the whole life cycle, we expressed the green fluorescent protein (GFP) and red fluorescent protein (RFP) in S. scitamineum MAT-1 and MAT-2 sporidia, respectively. Observation by epifluorescence microscope showed that conjugation tube formation and sporidia fusion occurred at 4 to 8 h, and formation of dikaryotic filaments was detected at 12 h after mating. The resultant teliospores, with diffused GFP and RFP, underwent meiosis as demonstrated by septated hypha with single fluorescent signal. We demonstrated that GFP- and RFP-tagged strains can be used to study the life cycle development of the fungal pathogen S. scitamineum, including the sexual mating and meiosis events. This dual-color imaging system would be a valuable tool for investigation of biotic and abiotic factors that might affect the fungal life cycle development and pathogenesis.

Development and Investigation of a Long-Range Time-of-Flight and Color Imaging System

2014 ◽  
Vol 44 (8) ◽  
pp. 1372-1382 ◽  
Author(s):  
Benjamin Langmann ◽  
Wolfgang Weihs ◽  
Klaus Hartmann ◽  
Otmar Loffeld
Keyword(s):  
Long Range ◽  
Imaging System ◽  
Time Of Flight ◽  
Color Imaging

Color Document Imaging with Amorphous Silicon Sensor Arrays

1994 ◽  
Vol 336 ◽  
Author(s):  
R. A. Street ◽  
X. D. Wu ◽  
R. Weisfield ◽  
S. Nelson ◽  
P. Nylen
Keyword(s):  
Amorphous Silicon ◽  
High Speed ◽  
Imaging System ◽  
Sensor Arrays ◽  
Color Imaging ◽  
Silicon Sensors ◽  
Imaging Properties ◽  
Color Filters ◽  
Illumination Source ◽  
Silicon Sensor

ABSTRACTWe describe the performance of an amorphous silicon imaging system designed for high speed (>10 frames/sec) scanning of a document. The system comprises a new page-sized sensor array with 1536×1920 pixels, an illumination source, and the readout electronics. With appropriate color filters, one can achieve color imaging of a document without the registration problems associated with linear scanners. We describe the color imaging properties and discuss how the color response, sensitivity and uniformity depend on the properties of the amorphous silicon sensors.

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