Formal framework for reasoning about the precision of dynamic analysis

Dynamic program analysis is extremely successful both in code debugging and in malicious code attacks. Fuzzing, concolic, and monkey testing are instances of the more general problem of analysing programs by dynamically executing their code with selected inputs. While static program analysis has a beautiful and well established theoretical foundation in abstract interpretation, dynamic analysis still lacks such a foundation. In this paper, we introduce a formal model for understanding the notion of precision in dynamic program analysis. It is known that in sound-by-construction static program analysis the precision amounts to completeness. In dynamic analysis, which is inherently unsound, precision boils down to a notion of coverage of execution traces with respect to what the observer (attacker or debugger) can effectively observe about the computation. We introduce a topological characterisation of the notion of coverage relatively to a given (fixed) observation for dynamic program analysis and we show how this coverage can be changed by semantic preserving code transformations. Once again, as well as in the case of static program analysis and abstract interpretation, also for dynamic analysis we can morph the precision of the analysis by transforming the code. In this context, we validate our model on well established code obfuscation and watermarking techniques. We confirm the efficiency of existing methods for preventing control-flow-graph extraction and data exploit by dynamic analysis, including a validation of the potency of fully homomorphic data encodings in code obfuscation

Pseudotumoural soft tissue lesions of the hand and wrist: a pictorial review

Mimickers of soft tissue tumours in the hand and wrist are more frequent than true neoplastic lesions. Pseudotumours belong to a large and heterogeneous group of disorders, varying from normal anatomical variants, cystic lesions, post-traumatic lesions, skin lesions, inflammatory and infectious lesions, non-neoplastic vascular lesions, metabolic disorders (crystal deposition disease and amyloidosis) and miscellaneous disorders. Although the imaging approach to pseudotumoural lesions is often very similar to the approach to “true” soft tissue tumoral counterparts, further management of these lesions is different. Biopsy should be performed only in doubtful cases, when the diagnosis is unclear. Therefore, the radiologist plays a pivotal role in the diagnosis of these lesions. Awareness of the normal anatomy and existence and common imaging presentation of these diseases, in combination with relevant clinical findings (clinical history, age, location and skin changes), enables the radiologist to make the correct diagnosis in most cases, thereby limiting the need for invasive procedures

Myocardial T1 mapping and determination of partition coefficients at 3 tesla: comparison between gadobenate dimeglumine and gadofosveset trisodium

Abstract Objective: To compare an albumin-bound gadolinium chelate (gadofosveset trisodium) and an extracellular contrast agent (gadobenate dimeglumine), in terms of their effects on myocardial longitudinal (T1) relaxation time and partition coefficient. Materials and Methods: Study subjects underwent two imaging sessions for T1 mapping at 3 tesla with a modified look-locker inversion recovery (MOLLI) pulse sequence to obtain one pre-contrast T1 map and two post-contrast T1 maps (mean 15 and 21 min, respectively). The partition coefficient was calculated as ΔR1myocardium /ΔR1blood , where R1 is 1/T1. Results: A total of 252 myocardial and blood pool T1 values were obtained in 21 healthy subjects. After gadolinium administration, the myocardial T1 was longer for gadofosveset than for gadobenate, the mean difference between the two contrast agents being −7.6 ± 60 ms (p = 0.41). The inverse was true for the blood pool T1, which was longer for gadobenate than for gadofosveset, the mean difference being 56.5 ± 67 ms (p < 0.001). The partition coefficient (λ) was higher for gadobenate than gadofosveset (0.41 vs. 0.33), indicating slower blood pool washout for gadofosveset than for gadobenate. Conclusion: Myocardial T1 times did not differ significantly between gadobenate and gadofosveset. At typical clinical doses of the contrast agents, partition coefficients were significantly lower for the intravascular contrast agent than for the extravascular agent

Five simultaneous artificial intelligence data challenges on ultrasound, CT, and MRI

International audiencePurposeThe goal of this data challenge was to create a structured dynamic with the following objectives: (1) teach radiologists the new rules of General Data Protection Regulation (GDPR), while building a large multicentric prospective database of ultrasound, computed tomography (CT) and MRI patient images; (2) build a network including radiologists, researchers, start-ups, large companies, and students from engineering schools, and; (3) provide all French stakeholders working together during 5 data challenges with a secured framework, offering a realistic picture of the benefits and concerns in October 2018.Materials and methodsRelevant clinical questions were chosen by the Société Francaise de Radiologie. The challenge was designed to respect all French ethical and data protection constraints. Multidisciplinary teams with at least one radiologist, one engineering student, and a company and/or research lab were gathered using different networks, and clinical databases were created accordingly.ResultsFive challenges were launched: detection of meniscal tears on MRI, segmentation of renal cortex on CT, detection and characterization of liver lesions on ultrasound, detection of breast lesions on MRI, and characterization of thyroid cartilage lesions on CT. A total of 5,170 images within 4 months were provided for the challenge by 46 radiology services. Twenty-six multidisciplinary teams with 181 contestants worked for one month on the challenges. Three challenges, meniscal tears, renal cortex, and liver lesions, resulted in an accuracy > 90%. The fourth challenge (breast) reached 82% and the lastone (thyroid) 70%.ConclusionTheses five challenges were able to gather a large community of radiologists, engineers, researchers, and companies in a very short period of time. The accurate results of three of the five modalities suggest that artificial intelligence is a promising tool in these radiology modalities