Medical Image Classification
Medical Image Classification is a task in medical image analysis that involves classifying medical images, such as X-rays, MRI scans, and CT scans, into different categories based on the type of image or the presence of specific structures or diseases. The goal is to use computer algorithms to automatically identify and classify medical images based on their content, which can help in diagnosis, treatment planning, and disease monitoring.
Papers
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All datasetsNCT-CRC-HE-100KIDRiDImageNetPCOS ClassificationCheXphotoGalaxy10 DECalsISIC 2017ISIC 2020 Challenge DatasetMalaria DatasetOASIS 3
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Efficientnet-b0 | Accuracy (%) | 95.59 | — | Unverified |
| 2 | ResNeXt-50-32x4d | Accuracy (%) | 95.46 | — | Unverified |
| 3 | RegNetY-3.2GF | Accuracy (%) | 95.42 | — | Unverified |
| 4 | ResNet-50 | Accuracy (%) | 94.72 | — | Unverified |
| 5 | DenseNet-169 | Accuracy (%) | 94.41 | — | Unverified |
| 6 | Res2Net-50 | Accuracy (%) | 93.37 | — | Unverified |
| 7 | ResNet-18 | Accuracy (%) | 92.66 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | ResNet-152 | Accuracy (% ) | 86.56 | — | Unverified |
| 2 | Beta-Rank | Accuracy | 81.88 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | InceptionV3 | 1:1 Accuracy | 90.2 | — | Unverified |
| 2 | EfficientNet B7 | 1:1 Accuracy | 88.9 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | PTRN | Mean AUC | 0.85 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Astroformer | Top-1 Accuracy (%) | 94.87 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Beta-Rank | Accuracy | 72.44 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | EfficientNet Ensemble | AUC | 0.95 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | SNAPSHOT ENSEMBLE | F1 score | 99.37 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | 3D CNN | AUC | 87 | — | Unverified |