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1 School of Interactive Computing, Georgia Tech 2 Intel Research Pittsburgh. Dermoscopic Interest Point Detector and Descriptor. Howard Zhou 1 , Mei Chen 2 , James M. Rehg 1. Skin cancer. Skin cancer : most common type of cancer ( > 1 million ). - PowerPoint PPT Presentation
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Dermoscopic Interest Point Detector and Descriptor
Howard Zhou1, Mei Chen2, James M. Rehg1
1School of Interactive Computing, Georgia Tech2Intel Research Pittsburgh
22009-07-01
Skin cancer Skin cancer : most common type of cancer ( > 1 million )
[ Top 5 categories of estimated annual cancer incidence for 2009 from National Cancer Institute ]
0 200,000 400,000 600,000 800,000 1,000,000 1,200,000
Bladder
Prostate
Breast
Lung
Skin
32009-07-01
Skin cancer Skin cancer : most common type of cancer ( > 1 million ) forms in tissues of the skin
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Skin lesions
42009-07-01
Skin cancer Skin cancer : most common type of cancer ( > 1 million ) forms in tissues of the skin
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Benign lesions
Skin cancer
52009-07-01
Skin cancer Skin cancer : most common type of cancer ( > 1 million ) forms in tissues of the skin
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Benign lesions
Skin cancer
Squamous cell carcinoma
Basal cell carcinoma
Melanoma
62009-07-01
Dermoscopy Non-invasive imaging technique Improve diagnostic accuracy by 30%
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Skin cancer
Squamous cell carcinoma
Basal cell carcinoma
Melanoma
72009-07-01
Dermoscopy
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Clinical view
Non-invasive imaging technique Improve diagnostic accuracy by 30%
82009-07-01
Dermoscopy
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermatoscope
Non-invasive imaging technique Improve diagnostic accuracy by 30% Microscope + light + liquid medium
92009-07-01
Dermoscopy Non-invasive imaging technique Improve diagnostic accuracy by 30% Microscope + light + liquid medium Reveal pigmented structures
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermatoscope
Dermoscopy view
102009-07-01
Dermoscopic features Pigmented structures revealed by dermoscopy
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
112009-07-01
Dermoscopic features Pigmented structures revealed by dermoscopy
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
122009-07-01
Dermoscopic features Pigmented structures revealed by dermoscopy
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
132009-07-01
Dermoscopic features Pigmented structures revealed by dermoscopy
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
142009-07-01
Dermoscopic features Pigmented structures revealed by dermoscopy
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
Negative network
152009-07-01
Dermoscopic features Pigmented structures revealed by dermoscopy [Betta et al. 2006], [Grana et al. 2006], [Iyatomi et al. 2007],
…
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
Negative network
162009-07-01
Dermoscopic features Over 100 dermoscopic features
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
Negative network
…
172009-07-01
Dermoscopic features
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
Negative network
…BW classifier
SLD classifier
BG classifier
NN classifier
… Over 100 dermoscopic features Multiple binary classifiers for each image
182009-07-01
Dermoscopic features
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
Negative network
…
General detector?
Generalized detector
192009-07-01
Dermoscopic features
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
Negative network
…
General detector?
Dermoscopic features consist of low level image characteristics (ridges, blobs, streaks, pigmentation,…)
Generalized detector
202009-07-01
Dermoscopic features
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
Negative network
…
General detector?
Dermoscopic features consist of low level image characteristics (ridges, blobs, streaks, pigmentation,…)
interest points
Generalized detector
212009-07-01
Dermoscopic Interest Point (DIP)
[ Image courtesy of “An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy” ]
Dermoscopy view
Blue-white veil
Scar-like depigmentation
Brown globules
Negative network
…
General detector: concentration/configuration of interest points
bag-of-visual-words approach
Dermoscopic features consist of low level image characteristics (ridges, blobs, streaks, pigmentation,…)
interest points
Generalized detector
222009-07-01
Dermoscopic Interest Point (DIP) Inspired by general interest point detector and descriptors
(SIFT & SURF) We propose Dermoscopic Interest Point (DIP)
detector - to extract these low level building blocks descriptor – for constructing a general visual vocabulary for
dermoscopic features
232009-07-01
Dermoscopic Interest Point (DIP) Compared to the general interest point detector and
descriptors (SIFT & SURF) Same key issues
Repeatable Distinctive Robust to noise and deformation (geometric and photometric)
Similar to SIFT & SURF Corners and blobs Scale and rotation invariant
In addition Curvilinear features (fibrillar pattern and radial streaming) Color component
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Detector Corners and blobs
Fast-Hessian detector [Bay, et al. 2006]
Hessian matrix
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Detector Corners and blobs
Fast-Hessian detector [Bay, et al. 2006]
Box filter approximation to replace Gaussian derivatives Fast using Integral image
Hessian matrix
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Detector Corners and blobs
Fast-Hessian detector [Bay, et al. 2006]
Curvilinear structures Curvilinear detector [Steger, 1996]
Hessian matrix
272009-07-01
Detector Corners and blobs
Fast-Hessian detector [Bay, et al. 2006]
Curvilinear structures Curvilinear detector [Steger, 1996]
Hessian matrix
282009-07-01
Detector Corners and blobs
Fast-Hessian detector [Bay, et al. 2006]
Curvilinear structures Curvilinear detector [Steger, 1996]
Hessian matrix
292009-07-01
Detector Corners and blobs
Fast-Hessian detector [Bay, et al. 2006]
Curvilinear structures Curvilinear detector [Steger, 1996]
Hessian matrix
302009-07-01
Descriptor Distinctiveness
Spatially localized information Distribution of gradient-related features Dermscopic: color features
Invariance (Repeatability) Relative strength to reduce the effect of photometric changes Relative orientation for rotation invariance
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Descriptor Distinctiveness
Spatially localized information Distribution of gradient-related features Dermscopic: color features
Invariance (Repeatability) Relative strength to reduce the effect of photometric changes Relative orientation for rotation invariance
To construct Reproducible orientation
322009-07-01
Descriptor Distinctiveness
Spatially localized information Distribution of gradient-related features Dermscopic: color features
Invariance (Repeatability) Relative strength to reduce the effect of photometric changes Relative orientation for rotation invariance
To construct Reproducible orientation
332009-07-01
Descriptor Distinctiveness
Spatially localized information Distribution of gradient-related features Dermscopic: color features
Invariance (Repeatability) Relative strength to reduce the effect of photometric changes Relative orientation for rotation invariance
To construct Reproducible orientation Feature vector
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Descriptor Orientation
For rotation invariance
Haar-wavelet responses in x and y direction (in a circular neighborhood)
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Descriptor Orientation
For rotation invariance
Haar-wavelet responses in x and y direction (in a circular neighborhood)
Reponses represented as 2D vectors dy
dx
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Descriptor Orientation
For rotation invariance
Haar-wavelet responses in x and y direction (in a circular neighborhood)
Reponses represented as 2D vectors
Average responses in a sliding window of 60 degree
dy
dx
372009-07-01
Descriptor Orientation
For rotation invariance
Haar-wavelet responses in x and y direction (in a circular neighborhood)
Reponses represented as 2D vectors
Average responses in a sliding window of 60 degree
The longest vector indicates the orientation
dy
dx
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Descriptor Descriptor components
Context of the descriptor: a square region oriented along the orientation (centered around the interest point)
Local statistics Uniform 4 x 4 subregions Intensity gradients (I): Sum of Haar-wavelet responses: dx, dy, |dx|,
|dy| Color statistics (C): Coarse color histogram of the region (alpha &
beta channels in L*a*b space)
[ Image courtesy of Bay et al. 2006]
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Dermoscopy Interest Point
402009-07-01
Dermoscopy specific Common interest point descriptor ignores linear
features
SURF DIP
412009-07-01
Experiment
422009-07-01
Conclusion A generalized framework for characterizing dermoscopic
features using Dermoscopic Interest Point (DIP) A feature detector and a descriptor specifically designed for
this purpose Initial experiments showed that our scheme achieves a
comparable level of invariance to lighting, scale, and rotation changes
432009-07-01
Future work Build a vocabulary of dermoscopic features using DIP Explore the possibility of using DIP in skin CAD related
applications: Dermoscopic feature extraction and classification Dermoscopy image registration Dermoscopy image search and retrieval via
dermoscopic features
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Acknowledgement Collaborators (in alphabetical order)
Dr. Laura K. Ferris M.D. Ph.D. UPMC Richard Gass, Intel Research Pittsburgh Casey Helfrich, Intel Research Pittsburgh
Many thanks to our anonymous reviewers for their helpful comments and suggestion
452009-07-01
Thank you
Thank you !
462009-07-01
Related publications Interest pointer detector and
descriptors Distinctive image features from scale-invariant
keypoints David G. LoweIntl. J. of Computer Vision (IJCV), 2004
Surf: Speeded up robust featuresHerbert Bay, Tinne tuytelaars, and Luc Van Gool,in Eur. Conf. on Computer Vision (ECCV), 2006
An unbiased detector of curvilinear structuresCarsten Steger,IEEE Trans. Pattern Anal. Machine Intell.(PAMI) 1996
472009-07-01
Outline Introduction Detector
Corners and blobs Curvilinear structures
Descriptor Orientation Descriptor components
Validation Conclusion
482009-07-01
Dermoscopic features A Pigmented Skin Lesion (PSL) typically has several
dermoscopic features Over 100 of these features
492009-07-01
Detecting line points
[ Steger 1998, ”An Unbiased Detector of Curvilinear Structures” ]
n(x)
Cross section
n(x)
L(x)
L’ = 0L’’ large
Curve
502009-07-01
Experiment
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