Art  Lind

Art Lind


A Python script to sort DICOM files

This article is a follow-up to my previous introduction to DICOM files. Special thanks to my good friend Dr. Gian Marco Conte for helping write this.

As a brief recap, DICOM files are the primary format for storing medical images. All clinical algorithms must be able to read and write DICOM. But these files can be challenging to organize. DICOM files have information associated with the image saved in a header, which can be extensive. Files are structured in 4 tiers:

  1. Patient
  2. Study
  3. Series
  4. Instance

In this tutorial, I’ll share some python code that reads a set of DICOM files, extracts the header information, and copies the files to a tiered folder structure that can be easily loaded for data science tasks.

There are many great resources available for parsing DICOM using Python or other languages. DicomSort has a flexible GUI which can organize files based on any field in the header (DicomSort is also available as a Python package with “pip install dicomsort”). I also want to credit this repo for getting me started with code for reading a DICOM pixel dataset. Finally, this great paper includes a section on image compression which I briefly mention here.

Ultimately I decided to write my own utility because I like knowing exactly what my code is doing, and it also provides an introduction to the DICOM header which is essential knowledge for any data scientist who works on medical imaging projects.

I’ve verified this code for both CT and MRI exams; it should work for any modality — Patient, Study, and Series information is reported for all DICOM files.

Required Code Packages

This code uses the Python package PyDicom for reading and writing DICOM files.

I want to briefly mention the GDCM package. DICOM files may have image compression performed on them either during storage or during transfer via the DICOM receiver. For example, at our institution, all DICOMs have JPEG2000 compression. GDCM is a C-based package that allows PyDicom to read these encrypted files. It’s available as a conda package (“conda install gdcm”) or built from source using cmake. I snuck a few lines in my code below which decompresses the pixel data using GDCM, so I don’t have to worry about it in the future.

#dicom #data-science #medical-imaging

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A Python script to sort DICOM files
Ray  Patel

Ray Patel


top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Ray  Patel

Ray Patel


Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Art  Lind

Art Lind


How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.


In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

  • md5
  • sha1
  • sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips

Art  Lind

Art Lind


Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

August  Larson

August Larson


Python for Beginners #2 — Importing files to python with pandas

Use pandas to upload CSV, TXT and Excel files

Story time before we begin

Learning Python isn’t the easiest thing to do. But consistency is really the key to arriving at a level that boosts your career.

We hear a lot about millennials wanting things to easy. In reality, there are a lot of young professionals who believe that they can do more for their companies but are being held back by the work cultures they are faced with at the onset of their careers.

Having been lucky enough to have found a job after my studies, I remember immediately feeling a wave of disappointment a very short while after starting my new job. I felt like a cog in a massive machine. I wasn’t really anything other than a ‘resource’. An extra 8–15 hours of daily man power depending on my boss’ whim.

The result, was the eventual disenchantment and lack of motivation simply because, for the most part, I was expected to be quiet and do my job in the hope of one day being senior enough to effect significant changes. And while the older generation would generally tell me to suck it up, I couldn’t see myself sucking it up for 5 years or more. I knew I’d get stale and afraid of change, much like those telling me to stay in my place.

For anyone in a similar situation,**_ do your best to improve on your skills _**and find an environment that works for you. That’s the whole purpose of these articles. To get you on your way to freedom.


For this demonstration, I’ll use data from this Kaggle competition. It’s a simple CSV file containing data on individuals in the Titanic and the different profiles i.e. (age, marital status etc.)

I want to import this file to python. I’ll show you how to do this alongside all the possible troubleshoots you may encounter.

Table of Contents

  1. Where should you put your files?
  2. Reading CSV and TXT files
  3. Reading excel (XLSX) files

#python #programming #pandas #python for beginners #importing files to python with pandas #python for beginners #2 — importing files to python with pandas