Background
Problem statement
Contribution
Paper organization
Related work
Methods
Contrast stretching
Lesion segmentation
Mean segmentation
Mean deviation based segmentation
Image fusion
X1∈i | X2∈j | S |
---|---|---|
0 | 0 | 0 |
0 | 1 | 1 |
1 | 0 | 1 |
1 | 1 | 1 |
Analysis
Image description | Similarity rate | Image description | Similarity rate |
---|---|---|---|
IMD038 | 95.69 | IMD199 | 94.70 |
IMD020 | 92.52 | IMD380 | 97.94 |
IMD039 | 91.35 | IMD385 | 94.37 |
IMD144 | 88.33 | IMD392 | 94.47 |
IMD203 | 86.44 | IMD394 | 96.96 |
IMD379 | 88.41 | IMD047 | 90.07 |
IMD429 | 94.87 | IMD075 | 95.85 |
IMD211 | 92.81 | IMD078 | 94.70 |
IMD285 | 95.59 | IMD140 | 96.94 |
IMD022 | 96.02 | IMD256 | 95.82 |
IMD025 | 96.35 | IMD312 | 96.04 |
IMD042 | 91.26 | IMD369 | 96.08 |
IMD173 | 96.04 | IMD376 | 93.07 |
IMD182 | 97.97 | IMD427 | 93.14 |
IMD430
|
98.10
| IMD168 | 92.88 |
Image representation
HOG features
Harlick features
Color features
Features fusion
Features selection
Results
Evaluation protocol
Datasets & results
PH2 Dataset
Method | Execution time /sec | Sensitivity (%) | Precision (%) | Specificity (%) | FNR (%) | FPR | Accuracy (%) |
---|---|---|---|---|---|---|---|
DT | 7 | 88.33 | 88.73 | 92.50 | 10.0 | 0.04 | 90.0 |
QDA | 2 | 90.83 | 89.40 | 91.20 | 9.0 | 0.04 | 91.0 |
Q-SVM | 2 | 95.83 | 96.60 | 98.70 | 3.0 | 0.01 | 97.0 |
LR | 6 | 92.10 | 92.76 | 96.96 | 6.0 | 0.02 | 94.0 |
N-B | 3 | 89.60 | 91.73 | 96.90 | 7.5 | 0.03 | 92.5 |
W-KNN | 2 | 91.67 | 92.33 | 96.20 | 6.5 | 0.02 | 93.5 |
EBT | 5 | 95.43 | 96.67 | 98.12 | 3.5 | 0.02 | 96.5 |
ESD | 10 | 94.20 | 94.53 | 97.50 | 4.5 | 0.02 | 95.5 |
C-KNN | 2 | 91.26 | 91.56 | 95.61 | 7.0 | 0.03 | 93.0 |
Multi-class SVM
|
1
|
96.67
|
97.06
|
98.74
|
2.5
|
0.01
|
97.5
|
Name | Features | Performance measures | |||||||
---|---|---|---|---|---|---|---|---|---|
Classification Method | Harlick | HOG | Color | Sensitivity (%) | Precision (%) | Specificity (%) | FNR (%) | FPR | Accuracy (%) |
Decision tree | ✓ | 67.53 | 67.50 | 70.05 | 31.50 | 0.16 | 68.5 | ||
✓ | 71.67 | 72.1 | 85.0 | 23.0 | 0.11 | 77.0 | |||
✓ | 87.93 | 86.93 | 86.9 | 12.5 | 0.06 | 87.5 | |||
Quadratic discriminant analysis | ✓ | 70.0 | 68.43 | 70.0 | 30.0 | 0.14 | 70.0 | ||
✓ | 74.60 | 75.83 | 88.15 | 20.0 | 0.09 | 80.0 | |||
✓ | 84.6 | 81.9 | 80.65 | 17.0 | 0.08 | 83.0 | |||
Quadratic SVM | ✓ | 68.33 | 70.27 | 76.25 | 28.5 | 0.14 | 71.5 | ||
✓ | 82.5 | 83.37 | 92.7 | 13.5 | 0.06 | 86.5 | |||
✓ | 93.77 | 93.33 | 94.44 | 6.0 | 0.03 | 94.0 | |||
Logistic regression | ✓ | 63.36 | 64.06 | 70.05 | 34.0 | 0.17 | 66.0 | ||
✓ | 86.27 | 85.83 | 91.9 | 11.5 | 0.09 | 88.5 | |||
✓ | 89.2 | 90.43 | 92.55 | 9.5 | 0.04 | 90.5 | |||
Naive bayes | ✓ | 62.9 | 62.9 | 66.85 | 35.5 | 0.18 | 64.5 | ||
✓ | 81.25 | 81.93 | 90.65 | 15.0 | 0.07 | 85.0 | |||
✓ | 87.93 | 87.63 | 90.65 | 11.0 | 0.06 | 89.0 | |||
Weighted KNN | ✓ | 66.67 | 67.5 | 72.5 | 31.0 | 0.16 | 69.0 | ||
✓ | 81.67 | 83.27 | 92.5 | 14.0 | 0.06 | 86.0 | |||
✓ | 90.87 | 90.83 | 92.55 | 8.5 | 0.03 | 91.5 | |||
Ensemble boosted tree | ✓ | 68.33 | 67.77 | 68.75 | 31.5 | 0.16 | 68.5 | ||
✓ | 80.67 | 82.57 | 91.3 | 15.0 | 0.07 | 85.0 | |||
✓ | 88.37 | 89.47 | 91.3 | 10.5 | 0.04 | 89.5 | |||
Ensemble subspace discriminant | ✓ | 68.76 | 68.4 | 71.9 | 30.0 | 0.15 | 70.0 | ||
✓ | 87.1 | 87.03 | 91.9 | 11.0 | 0.05 | 89.0 | |||
✓ | 92.9 | 94.7 | 96.9 | 5.5 | 0.03 | 94.1 | |||
Cubic KNN | ✓ | 65.43 | 66.4 | 71.9 | 32.0 | 0.16 | 68.0 | ||
✓ | 80.4 | 80.8 | 89.4 | 16.0 | 0.07 | 84.0 | |||
✓ | 90.3 | 89.83 | 91.7 | 9.5 | 0.04 | 90.5 | |||
Proposed | ✓ | 69.6 | 72.23 | 75.65 | 28.0 | 0.14 | 72.0 | ||
✓ | 86.27 | 87.37 | 94.4 | 10.5 | 0.02 | 89.5 | |||
✓ | 94.6 | 93.97 | 94.4 | 5.5 | 0.02 | 94.5 |
Confusion Matrix: Proposed features fusion and selection | ||||
Class | Tested images | Melanoma | Benign | Caricinoma |
Melanoma | 20 | 92.5% | 7.5% | |
Benign | 40 | 2.5% | 97.5% | |
Caricinoma | 40 | 100% | ||
Confusion matrix: Harlick features | ||||
Class | Total Images | Melanoma | Benign | Caricinoma |
Melanoma | 20 | 57.5% | 35% | 7.5% |
Benign | 40 | 8.8% | 68.8% | 22.5% |
Caricinoma | 40 | 3.8% | 13.8% | 82.5% |
Confusion matrix: HOG features | ||||
Class | Total Images | Melanoma | Benign | Caricinoma |
Melanoma | 20 | 70% | 30% | - |
Benign | 40 | 10% | 88.8% | 1.3% |
Caricinoma | 40 | - | - | 100% |
Confusion matrix: Color features | ||||
Class | Total Images | Melanoma | Benign | Caricinoma |
Melanoma | 20 | 95% | 5.0% | - |
Benign | 40 | 3.8% | 95% | 1.3% |
Caricinoma | 40 | 1.3% | 5.0% | 93.8% |
Method | Year | Sensitivity % | Specificity % | Accuracy % |
---|---|---|---|---|
Abuzaghleh et al. [26] | 2014 | - | - | 91 |
Barata et al. [27] | 2013 | 85 | 87 | 87 |
Abuza et al. [43] | 2015 | - | - | 96.5 |
Kruck et al. [44] | 2015 | 95 | 88.1 | - |
Rula et al. [45] | 2017 | 96 | 83 | - |
Waheed et al. [46] | 2017 | 97 | 84 | 96 |
Sath et al. [47] | 2017 | 96 | 97 | - |
GUU et al. [48] | 2017 | 94.43 | 81.01 | - |
Lei et al. [49] | 2016 | 87.50 | 93.13 | 92.0 |
MRastagoo et al. [50] | 2015 | 94 | 92 | - |
Proposed
|
2017
|
96.67
|
98.7
|
97.5
|
ISIC dataset
Method | Performance measures | |||||
---|---|---|---|---|---|---|
Sensitivity (%) | Precision (%) | Specificity (%) | FNR (%) | FPR | Accuracy (%) | |
Decision tree | 92.95 | 93.1 | 94.30 | 6.9 | 0.07 | 93.1 |
Quadratic discriminant analysis | 95.95 | 95.45 | 91.90 | 4.5 | 0.04 | 95.5 |
Quadratic SVM | 96.25 | 96.10 | 95.60 | 3.8 | 0.03 | 96.2 |
Logistic regression | 95.10 | 95.10 | 95.60 | 4.8 | 0.04 | 95.2 |
Naive bayes | 92.80 | 93.30 | 95.60 | 6.9 | 0.07 | 93.1 |
Weighted KNN | 95.10 | 95.10 | 95.60 | 4.8 | 0.04 | 95.2 |
Ensemble boosted tree | 95.10 | 95.10 | 95.60 | 4.80 | 0.04 | 95.2 |
Ensemble subspace discriminant | 95.10 | 95.10 | 95.60 | 4.8 | 0.04 | 95.2 |
Cubic KNN | 89.35 | 90.65 | 95.60 | 10.0 | 0.10 | 90.0 |
Proposed |
96.60
|
97.0
|
98.30
|
2.8
|
0.01
|
97.2
|
Classifier | Selected features | Performance measures | |||||||
---|---|---|---|---|---|---|---|---|---|
Color | HOG | Harlick | Sensitivity % | Precision % | Specificity | FNR % | FPR | Accuracy % | |
DT | ✓ | 89.4 | 89.65 | 0.919 | 10.3 | 0.105 | 89.7 | ||
✓ | 92.25 | 93.10 | 0.944 | 6.9 | 0.06 | 93.1 | |||
✓ | 80.95 | 82.15 | 0.888 | 18.3 | 0.18 | 81.7 | |||
QDA | ✓ | 86.05 | 86.05 | 0.875 | 13.8 | 0.13 | 86.2 | ||
✓ | 94.30 | 93.85 | 0.894 | 6.2 | 0.05 | 93.8 | |||
✓ | 70.73 | 73.25 | 0.769 | 26.6 | 0.26 | 73.4 | |||
Q-SVM | ✓ | 95.6 | 95.75 | 0.956 | 4.1 | 0.03 | 95.9 | ||
✓ | 95.5 | 95.46 | 0.956 | 4.5 | 0.04 | 95.5 | |||
✓ | 82.05 | 82.3 | 0.856 | 17.6 | 0.17 | 82.4 | |||
LR | ✓ | 92.05 | 92.7 | 0.956 | 7.6 | 0.07 | 92.4 | ||
✓ | 95.1 | 95.1 | 0.956 | 4.8 | 0.04 | 95.2 | |||
✓ | 81.45 | 82.25 | 0.875 | 17.9 | 0.18 | 82.1 | |||
N-B | ✓ | 90.9 | 91.8 | 0.956 | 8.6 | 0.08 | 91.4 | ||
✓ | 93.95 | 94.2 | 0.956 | 5.9 | 0.05 | 94.1 | |||
✓ | 82.2 | 83.95 | 0.913 | 16.9 | 0.03 | 83.1 | |||
W-KNN | ✓ | 90.9 | 91.9 | 0.956 | 8.6 | 0.08 | 91.4 | ||
✓ | 93.95 | 94.2 | 0.956 | 5.9 | 0.05 | 94.1 | |||
✓ | 81.15 | 84.2 | 0.938 | 17.6 | 0.08 | 82.4 | |||
EBT | ✓ | 91.45 | 91.85 | 0.994 | 8.3 | 0.08 | 91.7 | ||
✓ | 93.35 | 93.4 | 0.944 | 6.6 | 0.06 | 93.4 | |||
✓ | 81.45 | 82.25 | 0.875 | 17.9 | 0.18 | 82.1 | |||
ESD | ✓ | 86.95 | 88.05 | 0.931 | 12.4 | 0.125 | 87.6 | ||
✓ | 95.5 | 95.45 | 0.956 | 4.5 | 0.04 | 95.5 | |||
✓ | 78.0 | 79.5 | 0.875 | 21.0 | 0.21 | 79.0 | |||
Cubic KNN | ✓ | 93.25 | 93.5 | 0.95 | 6.6 | 0.06 | 93.4 | ||
✓ | 93.15 | 92.7 | 0.973 | 7.2 | 0.07 | 92.8 | |||
✓ | 76.6 | 76.6 | 0.788 | 23.1 | 0.23 | 76.9 | |||
Proposed | ✓ | 95.85 | 95.85 | 0.963 | 4.1 | 0.03 | 95.9 | ||
✓ | 97.1 | 96.75 | 0.963 | 3.8 | 0.02 | 96.2 | |||
✓ | 82.55 | 84.7 | 0.913 | 16.6 | 0.13 | 83.4 |
Class | Total images | Melanoma | Benign |
---|---|---|---|
Confusion matrix: Proposed features fusion and selection | |||
Melanoma | 130 | 99.2% | 1% |
Benign | 160 | 4.4% | 95.6% |
Confusion matrix: Harlick features | |||
Melanoma | 130 | 73.8% | 26.2% |
Benign | 160 | 8.8% | 91.3% |
Confusion matrix: HOG features | |||
Melanoma | 130 | 99.2% | 0.8% |
Benign | 160 | 5.0% | 95.0% |
Confusion matrix: Color features | |||
Melanoma | 130 | 96.2% | 3.8% |
Benign | 160 | 3.8% | 96.3% |
Method | Measures | |||||
---|---|---|---|---|---|---|
Sensitivity | Precision | Specificity | FNR | FPR | Accuracy | |
DT | 87.25 | 90.65 | 97.1 | 10.7 | 0.12 | 89.3 |
QDA | 79.75 | 88.60 | 99.3 | 16.3 | 0.19 | 83.7 |
QSVM | 98.05 | 98.40 | 99.3 | 1.7 | 0.02 | 98.3 |
LR | 94.8 | 96.35 | 99.3 | 4.3 | 0.04 | 95.7 |
N-B | 88.5 | 91.00 | 96.4 | 9.9 | 0.10 | 90.1 |
W-KNN | 83.85 | 91.20 | 100 | 12.9 | 0.16 | 87.1 |
EBT | 95.2 | 95.85 | 97.9 | 4.3 | 0.4 | 95.7 |
E-S-D | 89.6 | 89.75 | 92.1 | 9.9 | 0.09 | 90.1 |
L-KNN | 81.7 | 90.25 | 100 | 14.6 | 0.18 | 85.4 |
Proposed
|
97.85
|
98.60
|
100
|
1.7
|
0.02
|
98.3
|
Method | Features | Performance measures | |||||||
---|---|---|---|---|---|---|---|---|---|
Color | HOG | Harlick | Sensitivity (%) | Precision (%) | Specificity (%) | FNR (%) | FPR | Accuracy (%) | |
Decision tree | ✓ | 72.75 | 77.4 | 90.7 | 23.6 | 0.62 | 76.4 | ||
✓ | 70.15 | 69.4 | 69.3 | 30.0 | 0.30 | 70.0 | |||
✓ | 86.55 | 87.35 | 91.4 | 12.4 | 0.13 | 87.6 | |||
QDA | ✓ | 74.04 | 74.04 | 79.3 | 24.9 | 0.21 | 75.1 | ||
✓ | 77.4 | 88.45 | 100 | 18.0 | 0.22 | 82.0 | |||
✓ | 82.65 | 83.15 | 87.9 | 16.3 | 0.17 | 83.7 | |||
QSVM | ✓ | 73.7 | 77.25 | 89.3 | 23.2 | 0.73 | 76.8 | ||
✓ | 81.35 | 89.3 | 99.3 | 15.0 | 0.18 | 85.0 | |||
✓ | 94.45 | 95.8 | 98.6 | 4.7 | 0.05 | 95.3 | |||
LR | ✓ | 68.5 | 68.35 | 73.6 | 30.5 | 0.31 | 69.5 | ||
✓ | 78.5 | 88.9 | 100 | 17.2 | 0.21 | 82.8 | |||
✓ | 93.4 | 94.65 | 97.1 | 5.6 | 0.05 | 94.4 | |||
N-B | ✓ | 69.4 | 69.95 | 78.6 | 28.8 | 0.30 | 71.2 | ||
✓ | 76.7 | 76.7 | 81.4 | 22.3 | 0.22 | 77.7 | |||
✓ | 86.0 | 89.05 | 95.7 | 12.0 | 0.13 | 88.0 | |||
W-KNN | ✓ | 74.04 | 77.9 | 90.0 | 22.7 | 0.21 | 77.3 | ||
✓ | 80.8 | 87.15 | 97.1 | 15.9 | 0.17 | 84.1 | |||
✓ | 88.55 | 92.3 | 98.6 | 9.4 | 0.11 | 90.6 | |||
EBT | ✓ | 71.35 | 71.8 | 79.3 | 27.0 | 0.23 | 73.0 | ||
✓ | 80.8 | 83.8 | 92.9 | 17.2 | 0.17 | 82.8 | |||
✓ | 90.5 | 91.55 | 95.0 | 8.6 | 0.09 | 91.4 | |||
ESD | ✓ | 69.95 | 71.6 | 82.9 | 27.5 | 0.30 | 72.5 | ||
✓ | 60.2 | 74.5 | 85.0 | 24.9 | 0.27 | 75.1 | |||
✓ | 83.9 | 86.5 | 93.6 | 14.2 | 0.15 | 85.8 | |||
Cubic KNN | ✓ | 71.7 | 74.4 | 86.4 | 25.3 | 0.23 | 74.7 | ||
✓ | 80.15 | 87.4 | 97.9 | 16.3 | 0.19 | 83.7 | |||
✓ | 85.5 | 90.2 | 97.9 | 12.0 | 0.14 | 88.0 | |||
Proposed | ✓ | 73.65 | 78.5 | 91.4 | 22.7 | 0.22 | 77.3 | ||
✓ | 82.6 | 87.55 | 96.4 | 14.6 | 0.15 | 85.4 | |||
✓ | 95.2 | 95.85 | 97.9 | 4.3 | 0.04 | 95.7 |
Class | Total images | Melanoma | Benign |
---|---|---|---|
Confusion matrix: Proposed features fusion and selection | |||
Melanoma | 93 | 95.7% | 4.3% |
Benign | 140 | - | 100% |
Confusion matrix: Harlick features | |||
Melanoma | 93 | 55.9% | 44.1% |
Benign | 140 | 8.6% | 91.4% |
Confusion matrix: HOG features | |||
Melanoma | 93 | 68.8% | 31.2% |
Benign | 140 | 3.6% | 96.4% |
Confusion matrix: Color features | |||
Melanoma | 93 | 92.5% | 7.5% |
Benign | 140 | 2.1% | 97.9% |
ISBI - 2016 & 17
Method | Sensitivity (%) | Precision (%) | Specificity (%) | FNR (%) | FPR | Accuracy (%) | AUC |
---|---|---|---|---|---|---|---|
DT | 63.0 | 62.0 | 79.0 | 28.5 | 0.370 | 71.5 | 0.63 |
QDA | 68.0 | 65.5 | 79.0 | 26.4 | 0.320 | 73.6 | 0.74 |
Q-SVM | 68.5 | 78.5 | 95.0 | 17.7 | 0.315 | 82.3 | 0.81 |
LR | 67.0 | 65.0 | 79.0 | 26.1 | 0.330 | 72.9 | 0.69 |
NB | 74.5 | 77.0 | 91.5 | 17.1 | 0.255 | 82.9 | 0.84 |
W-KNN | 70.5 | 75.0 | 91.0 | 18.7 | 0.295 | 81.3 | 0.83 |
EBT | 66.0 |
80.0
|
97.0
| 18.3 |
0.034
| 81.7 | 0.79 |
ESDA | 72.5 | 55.0 | 90.0 | 18.5 | 0.275 | 81.5 | 0.83 |
Proposed |
75.5
| 78.0 | 93.0 |
16.8
| 0.270 |
83.2
|
0.85
|
Method | Sensitivity (%) | Precision (%) | Specificity (%) | FNR (%) | FPR | Accuracy (%) | AUC |
---|---|---|---|---|---|---|---|
DT | 74.5 | 75.0 | 77 | 25.5 | 0.255 | 74.8 | 0.77 |
QDA | 77.5 | 78.0 | 81 | 22.5 | 0.254 | 77.6 | 0.78 |
Q-SVM | 86.5 | 86.5 | 87 | 13.8 | 0.135 | 86.2 | 0.92 |
LR | 84.5 | 84.5 | 86 | 15.4 | 0.135 | 84.6 | 0.92 |
NB | 79.5 | 80.0 | 83 | 21.5 | 0.212 | 79.5 | 0.80 |
W-KNN | 87.5 | 88.0 | 88 | 12.2 | 0.125 | 87.8 | 0.92 |
EBT | 86.0 | 83.5 | 92 | 14.2 | 0.140 | 85.8 | 0.91 |
ESDA | 83.5 | 83.5 | 87.0 | 16.5 | 0.165 | 83.5 | 0.90 |
Proposed
|
88.5
|
88.0
|
91.0
|
11.8
|
0.120
|
88.2
|
0.93
|
Method | Performance measures | ||||||
---|---|---|---|---|---|---|---|
Sensitivity (%) | Precision (%) | Specificity (%) | FNR (%) | FPR | Accuracy (%) | AUC | |
DT | 87.5 | 88.0 | 86.0 | 12.4 | 0.125 | 87.6 | 0.86 |
QDA | 80.0 | 80.0 | 79.0 | 20.0 | 0.200 | 80.0 | 0.86 |
QSVM | 92.5 | 92.5 | 95.0 | 7.4 | 0.075 | 92.6 | 0.95 |
LR | 92.0 | 91.5 | 95.0 | 8.2 | 0.08 | 91.8 | 0.95 |
NB | 92.0 | 92.5 |
97.0
| 8.2 | 0.08 | 91.8 | 0.93 |
W-KNN | 88.5 | 88.5 | 91.0 | 11.6 | 0.115 | 88.4 | 0.88 |
EBT | 92.0 | 92.0 |
97.0
| 8.3 | 0.08 | 91.7 | 0.95 |
ESDA | 89.5 | 89.5 | 91.5 | 10.4 | 0.105 | 89.6 | 0.94 |
Proposed
|
93.0
|
93.5
|
97.0
|
6.8
|
0.07
|
93.2
|
0.96
|
ISBI 2016 | ||||
Classs | Classification class | TPR (%) | FNR (%) | |
Method | Benign | Melanoma | ||
Benign |
93%
| 3% | 93% | 3% |
Melanoma | 11% |
53%
| 53% | 11% |
ISBI 2017 | ||||
Class | Classification class | TPR (%) | FNR (%) | |
Benign | Melanoma | |||
Benign |
91%
| 9% | 91% | 9% |
Melanoma | 14% |
86%
| 86% | 14% |
Combined | ||||
Class | Classification class | TPR (%) | FNR (%) | |
Benign | Melanoma | |||
Benign |
97%
| 3% | 97% | 3% |
Melanoma | 11% |
89%
| 89% | 11% |