镜像自地址
https://github.com/xming521/CTAI.git
已同步 2025-12-06 06:36:49 +00:00
69 行
1.7 KiB
Python
69 行
1.7 KiB
Python
import SimpleITK as sitk
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import cv2
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import numpy as np
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image = sitk.ReadImage('../data/train/train/10087.dcm')
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image = sitk.GetArrayFromImage(image)[0, :, :]
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image[image < -300] = 0
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image[image > 300] = 0
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ROI = np.zeros(image.shape, np.uint8)
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# 获取图像中的像素数据
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slices = [image]
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# 复制Dicom图像中的像素数据
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img = slices[int(len(slices) / 2)].copy()
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img = np.uint8(img)
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kernel = np.ones((4, 4), np.uint8)
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img = cv2.dilate(img, kernel, iterations=1)
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# 对图像进行阈值分割
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ret, img = cv2.threshold(img, 150, 255, cv2.THRESH_BINARY_INV)
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xxx = img
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# 提取分割结果中的轮廓，并填充孔洞
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im2, contours, x = cv2.findContours(img.copy(), cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
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# 需要反色处理一下 现在找的是白色的 应该是黑色的
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# mask = np.zeros(img.shape, np.uint8)
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# for contour in contours:
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# cv2.fillPoly(mask, [contour], 255)
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# img[(mask > 0)] = 255
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area = []
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for c in contours:
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area.append(cv2.contourArea(c))
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cparea = area.copy()
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area.sort(reverse=True)
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for i in range(3, 8):
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max_idx = cparea.index(area[i])
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perimeter = cv2.arcLength(contours[max_idx], True)
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if area[i] > 5000 or perimeter > 500:
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continue
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print('周长', perimeter)
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cv2.drawContours(ROI, contours, max_idx, (220, 20, 60), -1)
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# max_idx = cparea.index(area[3])
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# cv2.drawContours(ROI, contours, max_idx, (220, 20, 60), -1)
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# cv2.drawContours(ROI, contours, max_idx, (220, 20, 60), -1)
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# 对分割结果进行形态学的开操作
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# kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (2, 2))
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# img = cv2.morphologyEx(img, cv2.MORPH_OPEN, kernel)
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# plt.figure(figsize=(10, 7))
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# plt.imshow(img, 'gray')
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# plt.title('Mask')
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# plt.show()
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cv2.imshow("Image", ROI)
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cv2.waitKey(0)
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