title: Machine learning approach to diagnose pneumoconiosis using GAN
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: ÐÐ¸Ð°Ð³Ð½Ð¾ÑÑÐ¸ÐºÐ° Ð¿Ð½ÐµÐ²Ð¼Ð¾ÐºÐ¾Ð½Ð¸Ð¾Ð·Ð° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð½Ð° GAN
Creators: name: ÐÐ¾ Ð¡Ð¸Ð½Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÐÐ°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÐÐ·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ
medical image detection
medical image generation
medical image segmentation
Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ðµ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ñ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹

description: Ð¯ ÑÐµÑÐ¸Ð» Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÑ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ LUNA16, Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ Ð¿Ð½ÐµÐ²Ð¼Ð¾Ð½Ð¸Ð¸ ÑÐµÐ½ÑÐ³ÐµÐ½Ð¾Ð²ÑÐºÐ¸Ñ ÑÐ½Ð¸Ð¼ÐºÐ¾Ð² Ð³ÑÑÐ´Ð½Ð¾Ð¹ ÐºÐ»ÐµÑÐºÐ¸ Ð¸ Ð½Ð°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ COVID-19 Ð¸ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐ°Ð» Ð´Ð°Ð½Ð½ÑÐµ Ð´Ð»Ñ Ð¿ÑÐµÐ¾Ð±ÑÐ°Ð·Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ¾ÑÐ¼Ð°ÑÐ° Ð´Ð°Ð½Ð½ÑÑ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¿Ð¾ÑÐ¾Ð³Ð¾Ð²Ð¾Ð¹ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸. Ð Ð·Ð°Ð´Ð°ÑÐµ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ Ð¼Ñ Ð² Ð¾ÑÐ½Ð¾Ð²Ð½Ð¾Ð¼ Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸Ð»Ð¸ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÑ, ÑÑÐ°Ð²Ð½Ð¸Ð²Ð°Ñ ÑÑÑÐµÐºÑ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ U-net Ð¸ Ð¿ÑÐµÐ´Ð»Ð°Ð³Ð°ÐµÐ¼Ð¾Ð¹ Ð½Ð°Ð¼Ð¸ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ PCFA-net, Ð¸ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¿Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÑÑ, ÑÑÐ¾ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ PCFA-net Ð½ÐµÐ¼Ð½Ð¾Ð³Ð¾ Ð»ÑÑÑÐµ. Ð Ð·Ð°Ð´Ð°ÑÐµ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð»ÐµÐ³Ð¾ÑÐ½ÑÑ ÑÐ·ÐµÐ»ÐºÐ¾Ð² ÑÐµÑÑ Ð±ÑÐ»Ð° Ð¿ÑÐ¾ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð° Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ ÑÑÐ½ÐºÑÐ¸Ð¹ Ð¿Ð¾ÑÐµÑÑ, Ð² Ð¾ÑÐ½Ð¾Ð²Ð½Ð¾Ð¼ Ð² ÑÐµÑÐµÐ²Ð¾Ð¹ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐµ YOLOv8, Ð¸ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð¸, ÑÑÐ¾ Ð¼Ð¾Ð´ÐµÐ»Ñ YOLOv8 Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ ÑÑÐ½ÐºÑÐ¸Ð¸ Ð¿Ð¾ÑÐµÑÑ EIOU ÑÐ°Ð±Ð¾ÑÐ°Ð»Ð° Ð»ÑÑÑÐµ Ð²ÑÐµÐ³Ð¾. ÐÐ»Ñ Ð·Ð°Ð´Ð°ÑÐ¸ Ð³ÐµÐ½ÐµÑÐ°ÑÐ¸Ð¸, Ð² Ð¾ÑÐ½Ð¾Ð²Ð½Ð¾Ð¼ Ð² ÑÐµÑÐµÐ²Ð¾Ð¹ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐµ SRWGAN, ÑÐ³ÐµÐ½ÐµÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½ÑÐµ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ ÑÑÐ°Ð½Ð¾Ð²ÑÑÑÑ Ð±Ð¾Ð»ÐµÐµ ÑÐµÑÐºÐ¸Ð¼Ð¸ Ð¿Ð¾ Ð¼ÐµÑÐµ ÑÐ²ÐµÐ»Ð¸ÑÐµÐ½Ð¸Ñ ÑÐ¸ÑÐ»Ð° Ð¸ÑÐµÑÐ°ÑÐ¸Ð¹, Ð°Ð½Ð°Ð»Ð¸Ð·Ð¸ÑÑÑÑÑÑ Ð¿Ð¾ÑÐµÑÐ¸ Ð³ÐµÐ½ÐµÑÐ°ÑÐ¾ÑÐ° Ð¸ Ð´Ð¸ÑÐºÑÐ¸Ð¼Ð¸Ð½Ð°ÑÐ¾ÑÐ° Ð²Ð¾ Ð²ÑÐµÐ¼Ñ Ð¿ÑÐ¾ÑÐµÑÑÐ° Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ ÑÐµÑÐ¸, Ð¸ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¿Ð¾ÐºÐ°Ð·ÑÐ²Ð°ÑÑ, ÑÑÐ¾ Ð½ÐµÑ Ð¿ÐµÑÐµÐ¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸Ð»Ð¸ Ð½ÐµÐ´Ð¾Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð½Ð°ÑÐµÐ¹ ÑÐµÑÐ¸ Ð²Ð¾ Ð²ÑÐµÐ¼Ñ Ð¸ÑÐµÑÐ°ÑÐ¸Ð¹, Ð¸ SRWGAN ÑÑÐ¿ÐµÑÐ½Ð¾ Ð·Ð°Ð²ÐµÑÑÐ°ÐµÑ Ð·Ð°Ð´Ð°ÑÑ ÑÐµÐºÐ¾Ð½ÑÑÑÑÐºÑÐ¸Ð¸. ÐÑ Ð½Ð°Ð´ÐµÐµÐ¼ÑÑ, ÑÑÐ¾ Ð½Ð°ÑÐ° ÑÐ°Ð±Ð¾ÑÐ° Ð±ÑÐ´ÐµÑ Ð¿Ð¾Ð»ÐµÐ·Ð½Ð° ÑÑÐµÐ½ÑÐ¼ Ð² Ð¾Ð±Ð»Ð°ÑÑÐ¸ Ð¾Ð±ÑÐ°Ð±Ð¾ÑÐºÐ¸ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹, Ð° ÑÐ°ÐºÐ¶Ðµ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½ÑÐºÐ¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹.
description: I chose to use the LUNA16 dataset, the pneumonia dataset of chest X-ray images, and the COVID-19 dataset, and processed the data for data format conversion as well as threshold segmentation. In the segmentation task, we mainly did experiments comparing the effect of U-net segmentation and our proposed PCFA-net segmentation, and the results show that PCFA-net segmentation is slightly better. In the lung nodule detection task, the network was tested using different loss functions mainly under the YOLOv8 network architecture, and the results showed that the YOLOv8 model using the EIOU loss function worked best. For the generation task, mainly under the SRWGAN network architecture, the generated images become clearer as the number of iterations increases, the loss of the generator and discriminator during the network training process is analysed, and the results show that there is no overfitting or underfitting of our network during iterations, and SRWGAN successfully completes the reconstruction task. We hope that our work can be useful for scholars in the field of medical image processing as well as medical image analysis.