jphdotam

jphdotam

import os
import math
from glob import glob

import pydicom
import numpy as np
import onnxruntime
from loguru import logger
from matplotlib import pyplot as plt
from skimage.transform import resize

jphdotam

jphdotam

# this is inspired by the official ImportDicomFiles.py - however, this is MUCH faster because
# it uses multiple workers to dramatically reduce IO bottlenecks
# it doesn't re-instantiate the Http() and headers for every file, rather every folder

# it does assume the input folders are structured in the orthanc format, e.g. /00/00/0000a8768bd86...
# and expects PATH_TO_SYNC to be something like:
## "/path/to/orthanc/root/*"  for all root folders
## "/path/to/orthanc/root/1*" for all folders beginning with 1
## "/path/to/orthanc/root/23" for root folder 23 only

jphdotam

package main

import (
	"fmt"
	"runtime"
	"sort"
	"sync"
)

var cores = runtime.NumCPU()

jphdotam

package main

import (
	"fmt"
	"runtime"
	"sort"
	"sync"
)

var cores = runtime.NumCPU()

jphdotam

import nimgl/[glfw, opengl]
import shader

type Vertex {.packed.} = object
    color: array[4, GLfloat]
    position: array[3, GLfloat]
proc initVertex(color: array[4, GLfloat], position: array[3, GLfloat]): Vertex = Vertex(color: color, position: position)

var verts: array[4, Vertex] = [
    initVertex([0.11f, 0.8f, 0.76f, 1.0f], [-0.5f, -0.5f, 0.0f]),

jphdotam

import os
import cv2
import glob
import pydicom
from pydicom.dicomdir import DicomDir
from pydicom.errors import InvalidDicomError

## EDIT THESE TWO LINES IF NEEDED:
FOLDER_PATH = "./dicom_study/" # Path to your folder of DICOMS; default assumes they're in a folder called 'dicom_study' in the same folder as this file
BLANK_PROPORTION = 0.05  # Set this to 0.1 to blank out top 10% of video (and therefore anonymise)