Tongue Tumor Detection in Medical Hyperspectral Images

Li, Zhi; Wang, Hongjun; Li, Qingli

doi:10.3390/s120100162

Cited by 122 publications

(84 citation statements)

References 26 publications

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“…It has exhibited potential in the diagnosis of head and neck cancer [3–8]. Computer assisted detection and quantitative analysis methods were proposed to detect cancer.…”

Section: Introductionmentioning

confidence: 99%

Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

Wang

et al. 2017

Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging

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Hyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-guided surgery. HSI acquires high-resolution images at hundreds of spectral bands, providing big data to differentiating different types of tissue. We proposed a deep learning based method for the detection of head and neck cancer with hyperspectral images. Since the deep learning algorithm can learn the feature hierarchically, the learned features are more discriminative and concise than the handcrafted features. In this study, we adopt convolutional neural networks (CNN) to learn the deep feature of pixels for classifying each pixel into tumor or normal tissue. We evaluated our proposed classification method on the dataset containing hyperspectral images from 12 tumor-bearing mice. Experimental results show that our method achieved an average accuracy of 91.36%. The preliminary study demonstrated that our deep learning method can be applied to hyperspectral images for detecting head and neck tumors in animal models.

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“…It has exhibited potential in the diagnosis of head and neck cancer [3–8]. Computer assisted detection and quantitative analysis methods were proposed to detect cancer.…”

Section: Introductionmentioning

confidence: 99%

Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

Wang

et al. 2017

Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging

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“…Liu et al . [12] measured and analyzed the reflectance spectra of human tongue based on the sparse representation of spectral information of each pixels. However, these classification methods only utilized the spectral information of individual pixels without considering the spatial relationship of neighboring pixels.…”

Section: Introductionmentioning

confidence: 99%

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging

Halig

Wang

et al. 2014

SPIE Proceedings

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As an emerging technology, hyperspectral imaging (HSI) combines both the chemical specificity of spectroscopy and the spatial resolution of imaging, which may provide a non-invasive tool for cancer detection and diagnosis. Early detection of malignant lesions could improve both survival and quality of life of cancer patients. In this paper, we introduce a tensor-based computation and modeling framework for the analysis of hyperspectral images to detect head and neck cancer. The proposed classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 96.97% and an average specificity of 91.42% in tumor-bearing mice. The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management.

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“…erlauben nur die Analyse eines sehr kleinen Schleimhautabschnittes mit einem Mikroendoskop. Die dritte Arbeit setzt ein makroskopisches System ein[ 37 ] . Auch hier wird mit Weißlicht als Anregung gearbeitet und ein Acousto-Optical Tunable Filter (AOTF) zur Auftrennung des refl ektierten Lichts eingesetzt.…”

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Hyperspectral Imaging in der Kopf-Hals-Onkologie

et al. 2013

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Hyperspectral Imaging has long been established in other scientific disciplines than medicine (e. g. earth science) as a means for objective classification of image data information. Some 10 years ago it was first introduced into medicine. Due to its immanent advantages - non-destructive specimen, compatibility with established optical tools (microscope, endoscope), objectivity, and user-independence - several attempts have been made in order to use its potential for the treatment of cancer patients. This publication reviews which methods have been developed for analogue issues in disciplines other than medicine, how these can be transferred into medicine, and what the perspectives are for the traditional innovative field of head-and-neck-oncology.

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Tongue Tumor Detection in Medical Hyperspectral Images

Cited by 122 publications

References 26 publications

Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging

Hyperspectral Imaging in der Kopf-Hals-Onkologie

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