Finished toolbox

Project.toml

@@ -3,6 +3,16 @@ uuid = "308a64e0-2da8-4ffc-993f-c99ea7c8dc9b"
 authors = ["Wenbo Li <[email protected]> and contributors"]
 version = "1.0.0-DEV"
 
+[deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DICOM = "a26e6606-dd52-5f6a-a97f-4f611373d757"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
+Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
+NIfTI = "a3a9e032-41b5-5fc4-967a-a6b7a19844d3"
+Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+
 [compat]
 julia = "1"
 

README.md

@@ -1,3 +0,0 @@
-# imageToolBox
-
-[![Build Status](https://github.com/Wenbo Li/imageToolBox.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/Wenbo Li/imageToolBox.jl/actions/workflows/CI.yml?query=branch%3Amain)

src/dicom_tools.jl

@@ -0,0 +1,116 @@
+using DICOM, Statistics
+
+"""
+    This function reads the dicom file.
+    - input:
+        1. path to the dicom file
+    - output:
+        1. dcm_data
+        2. SID
+        3. V_P
+        4. image
+"""
+function read_dicom(path_to_file::String)
+    dcm_data = dcm_parse(path_to_file)
+    # image
+    image = dcm_data[(0x7fe0, 0x0010)]
+    # v_p
+    LorR = ""
+    try
+        LorR = uppercase(dcm_data[(0x0020,0x0062)])
+    catch e
+        println("---------Error---------")
+        println(e)
+        println(curr_path)
+        println("---------Error---------")
+    end
+    V_P = ""
+    try
+        V_P = uppercase(dcm_data[(0x0018,0x5101)])
+    catch e
+        println("---------Error---------")
+        println(e)
+        println(curr_path)
+        println("---------Error---------")
+    end
+    curr_key = LorR*" "*V_P
+    # SID
+    sid = [(0x0010, 0x0020)]
+    return dcm_data, sid, curr_key, image
+end
+
+"""
+    This function gets the number of patches needed for a iamge.
+    - input:
+        1. Matrix of Float32: the image
+        2. Matrix of Float32: the roi
+        3. Matrix of Float32: the binary mask representing the breast area.
+    - optional input:
+        1. Float64: `thd`. The threshold of percentage of the white area. Default = 0.35
+        2. Int: 'patch_size'. The size of each patch. Default = 256
+    - output:
+        1. int: Number of without-BAC patches.
+        2. int: Number of with-BAC patches.
+"""
+function get_num_of_patches(img::Matrix{Float32}, lbl::Matrix{Float32}, mask::Matrix{Float32}; thd = 0.35, patch_size = 256)
+    patch_size_half = round(Int, patch_size/2)
+    s = size(img)
+    x = ceil(Int, s[1]/patch_size) + floor(Int, (s[1]-patch_size_half)/patch_size)
+    y = ceil(Int, s[2]/patch_size) + floor(Int, (s[2]-patch_size_half)/patch_size)
+    ct_empty, ct_non_empty = 0, 0
+    for i = 1 : x-1
+        x_start = 1+(i-1)*patch_size_half
+        x_end = x_start+patch_size-1
+        for j = 1 : y-1
+            y_start = 1+(j-1)*patch_size_half
+            y_end = y_start+patch_size-1
+            # check if this is forgounrd
+            if mean(mask[x_start:x_end, y_start:y_end]) > thd
+                # check if contains BAC
+                if sum(lbl[x_start:x_end, y_start:y_end]) > 0
+                    ct_non_empty += 1
+                else
+                    ct_empty += 1
+                end
+            end
+        end
+        # right col
+        y_start, y_end = s[2]-patch_size+1, s[2]
+        # check if this is forgounrd
+        if mean(mask[x_start:x_end, y_start:y_end]) > thd
+            # check if contains BAC
+            if sum(lbl[x_start:x_end, y_start:y_end]) > 0
+                ct_non_empty += 1
+            else
+                ct_empty += 1
+            end
+        end
+    end
+    # last row
+    x_start, x_end = s[1]-patch_size+1, s[1]
+    for j = 1 : y-1
+        y_start = 1+(j-1)*patch_size_half
+        y_end = y_start+patch_size-1
+        # check if this is forgounrd
+        if mean(mask[x_start:x_end, y_start:y_end]) > thd
+            # check if contains BAC
+            if sum(lbl[x_start:x_end, y_start:y_end]) > 0
+                ct_non_empty += 1
+            else
+                ct_empty += 1
+            end
+        end
+    end
+    # right col
+    y_start, y_end = s[2]-patch_size+1, s[2]
+    # check if this is forgounrd
+    if mean(mask[x_start:x_end, y_start:y_end]) > thd
+        # check if contains BAC
+        if sum(lbl[x_start:x_end, y_start:y_end]) > 0
+            ct_non_empty += 1
+        else
+            ct_empty += 1
+        end
+    end
+    return ct_empty, ct_non_empty
+end

src/imageToolBox.jl

@@ -1,5 +1,17 @@
 module imageToolBox
 
-# Write your package code here.
+using Pkg
+Pkg.activate("..")
+Pkg.instantiate()
 
-end
+include("dicom_tools.jl")
+include("nifty_tools.jl")
+include("png_tools.jl")
+include("other_tools.jl")
+
+export save_to_csv, get_last_edit_time, search_files_by_ext, search_files_by_name, binary_search_SID
+export zoom_pixel_values, copy_file, clean_directory, normalize_img
+export read_png, get_breast_mask
+export read_dicom, get_num_of_patches
+
+end