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Quantitative imaging studies of the pancreas have often targeted the three main anatomical segments, head, body, and tail, using manual region of interest strategies to assess geographic heterogeneity. Existing automated analyses have implemented whole-organ segmentation, providing overall quantification but failing to address spatial heterogeneity.To develop and validate an automated method for pancreas segmentation into head, body, and tail subregions in abdominal MRI.Retrospective.One hundred and fifty nominally healthy subjects from UK Biobank (100 subjects for method development and 50 subjects for validation). A separate 390 UK Biobank triples of subjects including type 2 diabetes mellitus (T2DM) subjects and matched nondiabetics.A 1.5 T, three-dimensional two-point Dixon sequence (for segmentation and volume assessment) and a two-dimensional axial multiecho gradient-recalled echo sequence.Pancreas segments were annotated by four raters on the validation cohort. Intrarater agreement and interrater agreement were reported using Dice overlap (Dice similarity coefficient [DSC]). A segmentation method based on template registration was developed and evaluated against annotations. Results on regional pancreatic fat assessment are also presented, by intersecting the three-dimensional parts segmentation with one available proton density fat fraction (PDFF) image.Wilcoxon signed rank test and Mann-Whitney U-test for comparisons. DSC and volume differences for evaluation. A P value lt; 0.05 was considered statistically significant.Good intrarater (DSC mean, head: 0.982, body: 0.940, tail: 0.961) agreement and interrater (DSC mean, head: 0.968, body: 0.905, tail: 0.943) agreement were observed. No differences (DSC, head: P = 0.4358, body: P = 0.0992, tail: P = 0.1080) were observed between the manual annotations and our method's segmentations (DSC mean, head: 0.965, body: 0.893, tail: 0.934). Pancreatic body PDFF was different between T2DM and nondiabetics matched by body mass index.The developed segmentation's performance was no different from manual annotations. Application on type 2 diabetes subjects showed potential for assessing pancreatic disease heterogeneity.4 TECHNICAL EFFICACY STAGE: 3.

This chapter covers the topic of program development and testing. An incremental approach to program development is introduced, in which a working version of the program is always maintained, starting with a trivial program, with additions to the program being made incrementally. Testing and validation are always performed after each increment. Error handling is also discussed, including ways to check that user input is valid, and MATLAB functions for reporting errors are described: the ‘error’, ‘warning’ and ‘try–catch’ statements. Program debugging is revisited and discussed in more detail along with common types of error that prevent programs from running successfully.

This chapter describes how file input/output operations can be performed using MATLAB. The difference between text and binary files is made clear and built-in MATLAB functions for reading data from and writing data to these files are introduced. Simple input/output operations for use with text files are described, such as load, save, dlmread and dlmwrite. More sophisticated and flexible functions such as fscanf, fprintf and textscan are also described. Functions for performing lower level file operations such as fgetl and feof are also covered. The concept of opening and closing of files is introduced. Built-in functions for working with binary files are described, such as fread and fwrite.

This chapter introduces the concept of control structures, which can be seen as the basic building blocks of computer programs. The concept of conditional control structures is described and it is demonstrated how MATLAB uses the ‘if-else’ and ‘switch’ statements to implement this idea. Different types of logical expression for use with ‘if’ statements are introduced, and it is also shown how logical operators can be used to combine different expressions into a single compound expression. Similarly, it is shown how MATLAB uses the ‘for’ and ‘while’ statements to implement the concept of an iteration control structure. Statements that unconditionally transfer control to another part of the program are also described, and MATLAB examples using the ‘break’ and ‘continue’ statements are provided. Finally, nesting of control structures within each other is described and its advantages and disadvantages outlined.