Useful Commands

DCMTK

Command line tools for DICOM manipulation, DICOM Toolkit, (DCMTK)

Query studies for a given medical record number

findscu    -P  -k 0008,0052=STUDY   -aet <AET> -aec <AEC> IPAddress Port# -k 0010,0020=<MRN>  -k 0020,000d -k 0008,1030 -k 0008,0020 -k 0008,0050

Query series for a given study UID

findscu    -S  -k 0008,0052=SERIES  -aet <AET> -aec <AEC> IPAddress Port# -k 0020,000D=<StudyUID> -k 0020,000E -k 0008,0060 -k 0010,0020=<MRN> -k 0008,103e

Query images for a given series UID

findscu -v -S  -k 0008,0052=IMAGE  -aet <AET> -aec <AEC> IPAddress Port# -k 0020,000D=<StudyUID> -k 0020,000e=<SeriesUID> -k 0008,1030 -k 0008,0020 -k 0008,0050 -k 0018,0050 -k 0008,0018

Transfer series for a given series UID

movescu -v -S  -k 0008,0052=SERIES  -aet <AET> -aec <AEC> IPAddress Port# -k 0020,000D=<StudyUID> -k 0020,000e=<SeriesUID>

SQL Database

Slicer, will create an SQL database of DICOM files to manage your project

First obtain a dicom dataset

   wget http://nrg.wustl.edu/projects/DICOM/sample1.zip

open Slicer's DICOM module
```
   vglrun /opt/apps/SLICER/Slicer-4.3.1-linux-amd64/Slicer
```
Select the data directory to import and the directory to store the database.
Slicer will build a ctkDICOM.sql SQLite file

The database is arranged in a hierarchy of SQL tables. A unique identifier (UID) is associated with each entry in the table.

Patients -> Studies -> Series -> Images

$ sqlite3 ctkDICOM.sql
SQLite version 3.6.22
Enter ".help" for instructions
Enter SQL statements terminated with a ";"
sqlite> select * from sqlite_master;
table|SchemaInfo|SchemaInfo|2|CREATE TABLE 'SchemaInfo' ( 'Version' VARCHAR(1024) NOT NULL )
table|Images|Images|3|CREATE TABLE 'Images' (   'SOPInstanceUID' VARCHAR(64)
NOT NULL,   'Filename' VARCHAR(1024) NOT NULL ,   'SeriesInstanceUID'
VARCHAR(64) NOT NULL ,   'InsertTimestamp' VARCHAR(20) NOT NULL ,   PRIMARY
KEY ('SOPInstanceUID') ) 
index|sqlite_autoindex_Images_1|Images|4|
table|Patients|Patients|5|CREATE TABLE 'Patients' (   'UID' INTEGER PRIMARY KEY AUTOINCREMENT,   'PatientsName' VARCHAR(255) NULL ,   'PatientID' VARCHAR(255) NULL ,   'PatientsBirthDate' DATE NULL ,   'PatientsBirthTime' TIME NULL ,   'PatientsSex' varchar(1) NULL ,   'PatientsAge' varchar(10) NULL ,   'PatientsComments' VARCHAR(255) NULL )
table|sqlite_sequence|sqlite_sequence|6|CREATE TABLE sqlite_sequence(name,seq)
table|Series|Series|7|CREATE TABLE 'Series' (   'SeriesInstanceUID' VARCHAR(64) NOT NULL ,   'StudyInstanceUID' VARCHAR(64) NOT NULL , 'SeriesNumber' INT NULL ,   'SeriesDate' DATE NULL ,   'SeriesTime' VARCHAR(20) NULL ,   'SeriesDescription' VARCHAR(255) NULL ,   'Modality' VARCHAR(20) NULL ,   'BodyPartExamined' VARCHAR(255) NULL , 'FrameOfReferenceUID' VARCHAR(64) NULL ,   'AcquisitionNumber' INT NULL , 'ContrastAgent' VARCHAR(255) NULL ,   'ScanningSequence' VARCHAR(45) NULL , 'EchoNumber' INT NULL ,   'TemporalPosition' INT NULL ,   PRIMARY KEY ('SeriesInstanceUID') )
index|sqlite_autoindex_Series_1|Series|8|
table|Studies|Studies|11|CREATE TABLE 'Studies' (   'StudyInstanceUID' VARCHAR(64) NOT NULL ,   'PatientsUID' INT NOT NULL ,   'StudyID' VARCHAR(255) NULL ,   'StudyDate' DATE NULL ,   'StudyTime' VARCHAR(20) NULL ,   'AccessionNumber' VARCHAR(255) NULL ,   'ModalitiesInStudy' VARCHAR(255) NULL ,   'InstitutionName' VARCHAR(255) NULL ,   'ReferringPhysician' VARCHAR(255) NULL ,   'PerformingPhysiciansName' VARCHAR(255) NULL , 'StudyDescription' VARCHAR(255) NULL ,   PRIMARY KEY ('StudyInstanceUID') )
index|sqlite_autoindex_Studies_1|Studies|12|
index|ImagesFilenameIndex|Images|14|CREATE UNIQUE INDEX 'ImagesFilenameIndex' ON 'Images' ('Filename')
index|ImagesSeriesIndex|Images|15|CREATE INDEX 'ImagesSeriesIndex' ON 'Images' ('SeriesInstanceUID')
index|SeriesStudyIndex|Series|16|CREATE INDEX 'SeriesStudyIndex' ON 'Series' ('StudyInstanceUID')
index|StudiesPatientIndex|Studies|17|CREATE INDEX 'StudiesPatientIndex' ON 'Studies' ('PatientsUID')
table|Directories|Directories|18|CREATE TABLE 'Directories' (   'Dirname' VARCHAR(1024) ,   PRIMARY KEY ('Dirname') )
index|sqlite_autoindex_Directories_1|Directories|19|

List all patients

sqlite> select * from Patients;
1|Sample Patient|Sample ID|1975-12-31||F||

List all studies for Patient with anonymized unique identifier=1

sqlite> select * from Studies where PatientsUID=1;
1.3.12.2.1107.5.2.32.35177.30000006121218324675000000034|1|1|2006-12-14|091206.156000|.||Hospital|||head^DHead

List all series for a given Study UID

sqlite> select * from Series where StudyInstanceUID='1.3.12.2.1107.5.2.32.35177.30000006121218324675000000034';
1.3.12.2.1107.5.2.32.35177.3.2006121409455295707319315.0.0.0|1.3.12.2.1107.5.2.32.35177.30000006121218324675000000034|6|2006-12-14|095148.593000|t2_spc_1mm_p2|MR|HEAD|1.3.12.2.1107.5.2.32.35177.1.20061214091206328.0.0.0|1||SE|1|0
1.3.12.2.1107.5.2.32.35177.3.2006121409371282268118605.0.0.0|1.3.12.2.1107.5.2.32.35177.30000006121218324675000000034|5|2006-12-14|094549.875000|t1_mpr_1mm_p2_pos50|MR|HEAD|1.3.12.2.1107.5.2.32.35177.1.20061214091206328.0.0.0|1||GR|1|0
1.3.12.2.1107.5.2.32.35177.3.2006121409284535196417894.0.0.0|1.3.12.2.1107.5.2.32.35177.30000006121218324675000000034|4|2006-12-14|093711.593000|t1_mpr_1mm_p2_pos50|MR|HEAD|1.3.12.2.1107.5.2.32.35177.1.20061214091206328.0.0.0|1||GR|1|0

List all images for a given Series UID

sqlite> select * from Images where SeriesInstanceUID='1.3.12.2.1107.5.2.32.35177.3.2006121409371282268118605.0.0.0' limit 3;
1.3.12.2.1107.5.2.32.35177.3.2006121409454232379618816|/home/bootcamp/Data/sample1/1.MR.head_DHead.5.33.20061214.091206.156000.2379618816.dcm|1.3.12.2.1107.5.2.32.35177.3.2006121409371282268118605.0.0.0|2014-08-16T12:20:00
1.3.12.2.1107.5.2.32.35177.3.2006121409454929962319192|/home/bootcamp/Data/sample1/1.MR.head_DHead.5.127.20061214.091206.156000.9962319192.dcm|1.3.12.2.1107.5.2.32.35177.3.2006121409371282268118605.0.0.0|2014-08-16T12:20:01
1.3.12.2.1107.5.2.32.35177.3.2006121409454611312919020|/home/bootcamp/Data/sample1/1.MR.head_DHead.5.84.20061214.091206.156000.1312919020.dcm|1.3.12.2.1107.5.2.32.35177.3.2006121409371282268118605.0.0.0|2014-08-16T12:20:01

Join across tables to summarize data

sqlite> select pt.patientid,sd.PatientsUID,se.seriesNumber,se.seriesdate,se.seriesinstanceuid 
        from studies sd 
        join series se on sd.Studyinstanceuid=se.studyinstanceuid 
        join patients pt on sd.patientsuid=pt.uid 
        limit 20 ;

Group Multiple Tables and write csv

.mode csv
.output segmentation.csv
select pt.PatientID, sd.OID, sd.StudyDate,
       t1.SeriesDescription , --t1.SeriesInstanceUID ,
       t2.SeriesDescription , --t2.SeriesInstanceUID ,
       fl.SeriesDescription , --fl.SeriesInstanceUID ,
       tc.SeriesDescription , --tc.SeriesInstanceUID ,
       sd.StudyDescription
from Studies   sd
join Patients  pt on sd.PatientsUID=pt.UID
join Series    t1 on sd.StudyInstanceUID=t1.StudyInstanceUID
join Series    t2 on sd.StudyInstanceUID=t2.StudyInstanceUID
join Series    fl on sd.StudyInstanceUID=fl.StudyInstanceUID
join Series    tc on sd.StudyInstanceUID=tc.StudyInstanceUID
where t1.SeriesDescription like '%T1%' and t1.SeriesDescription not like
'%+C%' and t1.SeriesDescription not like '%ther%' and t1.SeriesDescription
not like '%t-map%'
and   t1.SeriesDescription not like '%post%' and t1.SeriesDescription not
like '%fiber%' and t1.SeriesDescription not like '%CRANIOTOMY%'
and   t1.SeriesDescription not like '%dt1%'
and   t2.SeriesDescription like '%T2%' and t2.SeriesDescription not like
'%cor%' and t2.SeriesDescription not like '%T2*%' and t2.SeriesDescription
not like '%t-map%'
and   t2.SeriesDescription not like '%+c%' and   t2.SeriesDescription not
like '%flair%' and   t2.SeriesDescription not like '%weighted%'
and   t2.SeriesDescription not like '%2%*%' and   t2.SeriesDescription not
like '%star%'
and   fl.SeriesDescription like '%flair%'  and fl.SeriesDescription not like
'%cor%'
and   sd.StudyDescription like 'MRI%BRAIN%CONTRAST'
and   tc.SeriesDescription like '%T1%' and tc.SeriesDescription     like
'%+C%'
and   tc.SeriesDescription like '%sag%';
.output stdout

Access the database from MATLAB: http://sourceforge.net/projects/mksqlite/

GNU make

Use GNU make, to run multiple commands simulateously for batch processing on a single workstation. The below example will execute 4 processes.

$ make -j 4 -f parallel.makefile
echo target1 cmd1
echo target2 cmd1
echo target3 cmd1
echo target4 cmd1
target3 cmd1
target4 cmd1
target2 cmd1
target1 cmd1
echo target3 cmd2
echo target1 cmd2
echo target2 cmd2
echo target4 cmd2
target3 cmd2
target1 cmd2
echo target3 cmd3
echo target1 cmd3
target2 cmd2
target3 cmd3
echo target2 cmd3
target4 cmd2
echo target4 cmd3
target1 cmd3
target2 cmd3
target4 cmd3

The file parallel.makefile contains

all: target1 target2 target3 target4

target1:
	echo $@ cmd1
	echo $@ cmd2
	echo $@ cmd3
target2:
	echo $@ cmd1
	echo $@ cmd2
	echo $@ cmd3
target3:
	echo $@ cmd1
	echo $@ cmd2
	echo $@ cmd3
target4:
	echo $@ cmd1
	echo $@ cmd2
	echo $@ cmd3

Rsync

rsync -avz -v --include='*/' --include='fem_stats*.e' --exclude='*' source/ target/

Permissions

to set permissions recursively on a directory

chmod -R g+=rwXs *

or

find ./some/directory/ -type f -exec chmod g+rw {} \; #files

find ./some/directory/ -type d -exec chmod g+rwx {} \; #directories

umask 0027
for -rwxr-x--- (dir) -rw-r----- (file) default permissions

PYCLEWN

PYCLEWN debug: (1) start inferior_tty (2) attach pyclewn to inferior_tty

SCRGP2$ inferior_tty.py
'inferior_tty' two characters sequence commands:
    'C-a q' exit immediately
    'C-a c' close the slave pseudo terminal and exit after the gdb
inferior has
            terminated
    'C-a a' send a 'C-a' character

/dev/pts/15 pseudo terminal has been created.
Set the tty for the program being debugged with the gdb commands:
set inferior-tty /dev/pts/1
set environment TERM = screen

SCRGP2$ pyclewn --tty=/dev/pts/1 -a '--args ./FocusUltraSoundModel -snes_monitor -da_vec_type cusp -snes_converged_reason -ksp_monitor -log_summary -pc_type jacobi -dm_mat_type seqaijcusp'

Subsections