传统相机图像与智能手机图像用于眼睑肿瘤远程诊断的比较研究

数据集获取（Figshare）

• 源站标题：Comparative study between conventional camera images and smartphone images for eyelid tumor telediagnosis.
• DOI：10.6084/m9.figshare.19961920.v1
• 发布日期：2022-06-02
• 文件数：2 个
• 文件总体积：363.15 KB
• 源站页面：https://scielo.figshare.com/articles/dataset/Comparative_study_between_conventional_camera_images_and_smartphone_images_for_eyelid_tumor_telediagnosis_/19961920

命令行下载

curl -L -o "435ab9cf63a1aff9476fbd7f141e29d4cd4f9c89.jpg" "https://ndownloader.figshare.com/files/35525134"
curl -L -o "b2b234aaacdecfd675ff009b72f90089d4021862.jpg" "https://ndownloader.figshare.com/files/35525137"

文件清单

• 435ab9cf63a1aff9476fbd7f141e29d4cd4f9c89.jpg（183.56 KB）
• b2b234aaacdecfd675ff009b72f90089d4021862.jpg（179.59 KB）

文件总体积 363.15 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

ABSTRACT Objective: to compare the accuracy of eyelid tumor diagnosis obtained by evaluating conventional camera images with the ones obtained by evaluating smartphone images. Methods: from January 2016 to July 2017, 36 patients underwent face-to-face external assessments and biomicroscopic examinations to establish clinical diagnoses. The lesions were photographed using Canon PowerShot SX530 HS Digital Camera (16.8 Megapixels) and Samsung GALAXY S4 smartphone camera. All lesions were resected and submitted to anatomopathological examinations. Preoperative images were sent to two specialists in eyelid diseases and then remotely analyzed. Data from in-person diagnoses and telediagnoses were compared with the gold standard of histological diagnosis. Results: the most frequent lesions were basal cell carcinoma (33.3%), actinic keratosis (19.4%), and nevus (13.9%). Kappa coefficient for the diagnosis of malignant lesion showed agreement between the two tele-evaluators in the conventional digital camera images (0.68) and in the smartphone images (0.78). The face-to-face examiner’s accuracy was of 94.4%; the tele-evaluators’ accuracy in the conventional digital camera images was of 83.3% and in the smartphone images varied from 80.6% to 86.1%. Comparing the in-person diagnoses with the telediagnoses (obtained by evaluating conventional digital camera images or smartphone images), there was no significant difference in the hit rates. Conclusion: for eyelid tumor telediagnosis, images obtained using smartphone camera were equivalent to those obtained using conventional digital camera.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.19961920.v1（source: https://scielo.figshare.com/articles/dataset/Comparative_study_between_conventional_camera_images_and_smartphone_images_for_eyelid_tumor_telediagnosis_/19961920）。