def convert_sax_images(rescale=True, base_size=256, crop_size=256):
target_dir = settings.BASE_PREPROCESSEDIMAGES_DIR
print("Deleting old files..")
helpers.delete_files(target_dir, "*.png")
print("patient\trows\tcols\tspacing\tfile_name")
file_count = 0
for dicom_data in helpers.enumerate_sax_files():
file_count += 1
if dicom_data.in_plane_encoding_direction not in ["ROW", "COL"]:
raise Exception("ROW,COL")
if dicom_data.spacing[0] != dicom_data.spacing[1]:
raise Exception("Data spacings not equal")
print(
str(dicom_data.patient_id) + "\t" + str(dicom_data.rows) + "\t" +
str(dicom_data.columns) + "\t" + str(dicom_data.series_number) +
"\t" + str(dicom_data.spacing) + "\t" +
str(dicom_data.slice_thickness) + "\t" +
str(dicom_data.sequence_name) + "\t" +
str(dicom_data.image_position) + "\t" +
str(dicom_data.slice_location) + "\t" +
dicom_data.in_plane_encoding_direction)
location_id = int(dicom_data.slice_location) + 10000
time_id = dicom_data.create_time
location_id_str = str(location_id).rjust(5, '0')
img_path = target_dir + str(dicom_data.patient_id).rjust(
4, '0') + "_" + dicom_data.series_description.rjust(
8, '0') + "_" + str(dicom_data.instance_number).rjust(
2, '0'
) + "_" + location_id_str + "_" + dicom_data.file_name.replace(
".dcm", ".png")
scipy.misc.imsave(img_path, dicom_data.pixel_array)
img = cv2.imread(img_path, 0)
if dicom_data.in_plane_encoding_direction == "COL":
# rotate counter clockwise when image is column oriented..
img = cv2.transpose(img)
img = cv2.flip(img, 0)
print("")
if rescale:
scale = dicom_data.spacing[0]
img = cv2.resize(img, (0, 0), fx=scale, fy=scale)
sq_img = get_square_crop(img, base_size=base_size, crop_size=crop_size)
clahe = cv2.createCLAHE(tileGridSize=(1, 1))
cl_img = clahe.apply(sq_img)
cv2.imwrite(img_path, cl_img)
def convert_sax_images(dicom_dir, rescale=True, crop_size=256):
"""
:param dicom_dir: 文件路径
:param rescale:
:param base_size:
:param crop_size:
:return:
"""
"""读取dicom文件，并将其转换为png格式，裁剪，翻转等，然后将图像存储起来"""
target_dir = settings.BASE_PREPROCESSEDIMAGES_DIR
file_count = 0
for dicom_data in helpers.enumerate_sax_files(dicom_dir):
file_count += 1
if dicom_data.in_plane_encoding_direction not in ["ROW", "COL"]:
print("Error: plane_encoding_direction", dicom_data.file_name)
raise Exception("ROW,COL")
if dicom_data.spacing[0] != dicom_data.spacing[1]:
print("Error: spacing")
raise Exception("Data spacings not equal")
if file_count % 100 == 0:
print(str(dicom_data.patient_id) + "\t" + str(dicom_data.series_number))
location_id = int(dicom_data.slice_location) + 1000 #负数变正数
location_id_str = str(location_id).rjust(4, '0')
#rjust 字符串的长度统一
#命名规则
img_path = target_dir + str(dicom_data.patient_id).rjust(4, '0') + '_'\
+ str(dicom_data.series_number).rjust(2, '0') +"_" \
+str(dicom_data.instance_number).rjust(3,'0') + ".png"
#img = Image.fromarray(dicom_data.pixel_array) #数组转图像
scipy.misc.imsave(img_path, dicom_data.pixel_array) #将数组存为图像
img = cv2.imread(img_path, 0)
if dicom_data.in_plane_encoding_direction == "COL":
# rotate counter clockwise when image is column oriented..
img = cv2.transpose(img) #图像转置，将x，y互换
img = cv2.flip(img, 0) #纵向翻转图像
if rescale: #将图像从像素大小转为物理大小
scale = dicom_data.spacing[0]
img = cv2.resize(img, (0, 0), fx=scale, fy=scale)
sq_img = get_square_crop(img, crop_size=crop_size)
clahe = cv2.createCLAHE(tileGridSize=(1, 1)) #直方图均衡化，以小块为单位
cl_img = clahe.apply(sq_img)
cv2.imwrite(img_path, cl_img)
def create_csv_data():
print("Creating csv file from dicom data")
row_no = 0
with open(settings.BASE_DIR + "dicom_data.csv", "wb") as csv_file:
csv_writer = csv.writer(csv_file,
delimiter=";",
quoting=csv.QUOTE_MINIMAL)
csv_writer.writerow([
"patient_id", "slice_no", "frame_no", "rows", "columns", "spacing",
"slice_thickness", "slice_location", "slice_location2", "plane",
"image_position", "sv", "time", "manufact", "modelname", "age",
"birth", "sex", "file_name", "angle", "o1", "o2", "o3", "o4", "o5",
"o6"
])
for dicom_data in helpers.enumerate_sax_files():
row_no += 1
if row_no % 1000 == 0:
print(row_no)
csv_writer.writerow([
str(dicom_data.patient_id),
str(dicom_data.series_number),
str(dicom_data.instance_number),
str(dicom_data.rows),
str(dicom_data.columns),
str(dicom_data.spacing[0]),
str(dicom_data.slice_thickness),
str(dicom_data.slice_location),
str(dicom_data.get_location()),
dicom_data.in_plane_encoding_direction,
str(dicom_data.image_position),
str(dicom_data.get_value("SequenceVariant")),
str(dicom_data.get_value("InstanceCreationTime")),
str(dicom_data.get_value("Manufacturer")),
str(dicom_data.get_value("ManufacturerModelName")),
str(dicom_data.get_value("PatientAge")),
str(dicom_data.get_value("PatientBirthDate")),
str(dicom_data.get_value("PatientSex")),
dicom_data.file_name.replace(".dcm", ""),
str(dicom_data.get_value("FlipAngle")),
str(round(dicom_data.image_orientation_patient[0], 2)),
str(round(dicom_data.image_orientation_patient[1], 2)),
str(round(dicom_data.image_orientation_patient[2], 2)),
str(round(dicom_data.image_orientation_patient[3], 2)),
str(round(dicom_data.image_orientation_patient[4], 2)),
str(round(dicom_data.image_orientation_patient[5], 2))
])
def convert_sax_images(rescale=True, base_size=256, crop_size=256):
target_dir = settings.BASE_PREPROCESSEDIMAGES_DIR
print "Deleting old files.."
helpers.delete_files(target_dir, "*.png")
print "patient\trows\tcols\tspacing\tfile_name"
file_count = 0
for dicom_data in helpers.enumerate_sax_files():
file_count += 1
if dicom_data.in_plane_encoding_direction not in ["ROW", "COL"]:
raise Exception("ROW,COL")
if dicom_data.spacing[0] != dicom_data.spacing[1]:
raise Exception("Data spacings not equal")
print str(dicom_data.patient_id) + "\t" + str(dicom_data.rows) + "\t" + str(dicom_data.columns) + "\t" + str(dicom_data.series_number) + "\t" + str(dicom_data.spacing) + "\t" + str(dicom_data.slice_thickness) + "\t" + str(dicom_data.sequence_name) + "\t" + str(dicom_data.image_position) + "\t" + str(dicom_data.slice_location) + "\t" + dicom_data.in_plane_encoding_direction
location_id = int(dicom_data.slice_location) + 10000
time_id = dicom_data.create_time
location_id_str = str(location_id).rjust(5, '0')
img_path = target_dir + str(dicom_data.patient_id).rjust(4, '0') + "_" + dicom_data.series_description.rjust(8, '0') + "_" + str(dicom_data.instance_number).rjust(2, '0') + "_" + location_id_str + "_" + dicom_data.file_name.replace(".dcm", ".png")
scipy.misc.imsave(img_path, dicom_data.pixel_array)
img = cv2.imread(img_path, 0)
if dicom_data.in_plane_encoding_direction == "COL":
# rotate counter clockwise when image is column oriented..
img = cv2.transpose(img)
img = cv2.flip(img, 0)
print ""
if rescale:
scale = dicom_data.spacing[0]
img = cv2.resize(img, (0, 0), fx=scale, fy=scale)
sq_img = get_square_crop(img, base_size=base_size, crop_size=crop_size)
clahe = cv2.createCLAHE(tileGridSize=(1, 1))
cl_img = clahe.apply(sq_img)
cv2.imwrite(img_path, cl_img)
def create_csv_data(data_dir):
print("Creating csv file from dicom data")
row_no = 0
with open("dicom_data.csv", "w", newline='') as csv_file:
csv_writer = csv.writer(csv_file, delimiter=",", quoting=csv.QUOTE_MINIMAL)
csv_writer.writerow(["patient_id", "slice_no", "frame_no",
"spacing","slice_thickness", "slice_location", "time"])
for dicom_data in helpers.enumerate_sax_files(data_dir):
row_no += 1
if row_no % 1000 == 0:
print(row_no)
csv_writer.writerow([
str(dicom_data.patient_id), #病人编号
str(dicom_data.series_number), #层号，与文件夹数字一致，eg：sax_5中的文件seriesNumber都是5
str(dicom_data.instance_number), #在同一层中的不同时间下的编号。
str(dicom_data.spacing[0]), #像素的物理间距，即实际大小
str(dicom_data.slice_thickness), #层厚
str(dicom_data.slice_location), #当前层的位置，单位mm, 同一层一致
str(dicom_data.get_value("InstanceCreationTime")), #当前图片的时间
])
def create_csv_data():
print "Creating csv file from dicom data"
row_no = 0
with open(settings.BASE_DIR + "dicom_data.csv", "wb") as csv_file:
csv_writer = csv.writer(csv_file, delimiter=";", quoting=csv.QUOTE_MINIMAL)
csv_writer.writerow(["patient_id", "slice_no", "frame_no", "rows", "columns", "spacing", "slice_thickness", "slice_location", "slice_location2", "plane", "image_position", "sv", "time", "manufact", "modelname", "age", "birth", "sex", "file_name", "angle", "o1", "o2", "o3", "o4", "o5","o6"])
for dicom_data in helpers.enumerate_sax_files():
row_no += 1
if row_no % 1000 == 0:
print row_no
csv_writer.writerow([
str(dicom_data.patient_id),
str(dicom_data.series_number),
str(dicom_data.instance_number),
str(dicom_data.rows),
str(dicom_data.columns),
str(dicom_data.spacing[0]),
str(dicom_data.slice_thickness),
str(dicom_data.slice_location),
str(dicom_data.get_location()),
dicom_data.in_plane_encoding_direction,
str(dicom_data.image_position),
str(dicom_data.get_value("SequenceVariant")),
str(dicom_data.get_value("InstanceCreationTime")),
str(dicom_data.get_value("Manufacturer")),
str(dicom_data.get_value("ManufacturerModelName")),
str(dicom_data.get_value("PatientAge")),
str(dicom_data.get_value("PatientBirthDate")),
str(dicom_data.get_value("PatientSex")),
dicom_data.file_name.replace(".dcm", ""),
str(dicom_data.get_value("FlipAngle")),
str(round(dicom_data.image_orientation_patient[0], 2)),
str(round(dicom_data.image_orientation_patient[1], 2)),
str(round(dicom_data.image_orientation_patient[2], 2)),
str(round(dicom_data.image_orientation_patient[3], 2)),
str(round(dicom_data.image_orientation_patient[4], 2)),
str(round(dicom_data.image_orientation_patient[5], 2))
])
