Liver lesion segmentation informed by joint liver segmentation

We propose a model for the joint segmentation of the liver and liver lesions in computed tomography (CT) volumes. We build the model from two fully convolutional networks, connected in tandem and trained together end-to-end. We evaluate our approach on the 2017 MICCAI Liver Tumour Segmentation Challenge, attaining competitive liver and liver lesion detection and segmentation scores across a wide range of metrics. Unlike other top performing methods, our model output post-processing is trivial, we do not use data external to the challenge, and we propose a simple single-stage model that is trained end-to-end. However, our method nearly matches the top lesion segmentation performance and achieves the second highest precision for lesion detection while maintaining high recall.Comment: Late upload of conference version (ISBI

The Value of Information Concealment

We consider a revenue optimizing seller selling a single item to a buyer, on whose private value the seller has a noisy signal. We show that, when the signal is kept private, arbitrarily more revenue could potentially be extracted than if the signal is leaked or revealed. We then show that, if the seller is not allowed to make payments to the buyer, the gap between the two is bounded by a multiplicative factor of 3, if the value distribution conditioning on each signal is regular. We give examples showing that both conditions are necessary for a constant bound to hold. We connect this scenario to multi-bidder single-item auctions where bidders' values are correlated. Similarly to the setting above, we show that the revenue of a Bayesian incentive compatible, ex post individually rational auction can be arbitrarily larger than that of a dominant strategy incentive compatible auction, whereas the two are no more than a factor of 5 apart if the auctioneer never pays the bidders and if each bidder's value conditioning on the others' is drawn according to a regular distribution. The upper bounds in both settings degrade gracefully when the distribution is a mixture of a small number of regular distributions

Cryptanalysis of a technique to transform discrete logarithm based cryptosystems into identity-based cryptosystems

In this paper we analyse a technique designed to transform any discrete logarithm based cryptosystem into an identity-based cryptosystem. The transformation method is claimed to be efficient and secure and to eliminate the need to invent new identity-based cryptosystems. However, we show that the identity-based cryptosystem created by the proposed transformation method suffers from a number of security and efficiency problems

Improved Hardness of BDD and SVP Under Gap-(S)ETH

We show improved fine-grained hardness of two key lattice problems in the $\ell_p$ norm: Bounded Distance Decoding to within an $\alpha$ factor of the minimum distance ($\mathrm{BDD}_{p, \alpha}$) and the (decisional) $\gamma$-approximate Shortest Vector Problem ($\mathrm{SVP}_{p,\gamma}$), assuming variants of the Gap (Strong) Exponential Time Hypothesis (Gap-(S)ETH). Specifically, we show: 1. For all $p \in [1, \infty)$, there is no $2^{o(n)}$-time algorithm for $\mathrm{BDD}_{p, \alpha}$ for any constant $\alpha > \alpha_\mathsf{kn}$, where $\alpha_\mathsf{kn} = 2^{-c_\mathsf{kn}} < 0.98491$ and $c_\mathsf{kn}$ is the $\ell_2$ kissing-number constant, unless non-uniform Gap-ETH is false. 2. For all $p \in [1, \infty)$, there is no $2^{o(n)}$-time algorithm for $\mathrm{BDD}_{p, \alpha}$ for any constant $\alpha > \alpha^\ddagger_p$, where $\alpha^\ddagger_p$ is explicit and satisfies $\alpha^\ddagger_p = 1$ for $1 \leq p \leq 2$, $\alpha^\ddagger_p 2$, and $\alpha^\ddagger_p \to 1/2$ as $p \to \infty$, unless randomized Gap-ETH is false. 3. For all $p \in [1, \infty) \setminus 2 \mathbb{Z}$ and all $C > 1$, there is no $2^{n/C}$-time algorithm for $\mathrm{BDD}_{p, \alpha}$ for any constant $\alpha > \alpha^\dagger_{p, C}$, where $\alpha^\dagger_{p, C}$ is explicit and satisfies $\alpha^\dagger_{p, C} \to 1$ as $C \to \infty$ for any fixed $p \in [1, \infty)$, unless non-uniform Gap-SETH is false. 4. For all $p > p_0 \approx 2.1397$, $p \notin 2\mathbb{Z}$, and all $C > C_p$, there is no $2^{n/C}$-time algorithm for $\mathrm{SVP}_{p, \gamma}$ for some constant $\gamma > 1$, where $C_p > 1$ is explicit and satisfies $C_p \to 1$ as $p \to \infty$, unless randomized Gap-SETH is false.Comment: ITCS 202

Security of the Lin-Lai smart card based user authentication scheme

The remote user authentication scheme of Lin and Lai, that uses a smart card and a fingerprint measurement, is reviewed and shown to possess significant security issues

Eating As Treatment (EAT): A Stepped-Wedge, Randomized Controlled Trial of a Health Behavior Change Intervention Provided by Dietitians to Improve Nutrition in Patients With Head and Neck Cancer Undergoing Radiation Therapy (TROG 12.03)

Purpose: Malnutrition in head and neck cancer (HNC) treatment is common and associated with poorer morbidity and mortality outcomes. This trial aimed to improve nutritional status during radiation therapy (RT) using a novel method of training dietitians to deliver psychological techniques to improve nutritional behaviors in patients with HNC. Methods and Materials: This trial used a stepped-wedge, randomized controlled design to assess the efficacy of the Eating As Treatment (EAT) program. Based on motivational interviewing and cognitive behavioral therapy, EAT was designed to be delivered by oncology dietitians and integrated into their clinical practice. During control steps, dietitians provided treatment as usual, before being trained in EAT and moving into the intervention phase. The training was principles based and sought to improve behavior-change skills rather than provide specific scripts. Patients recruited to the trial (151 controls, 156 intervention) were assessed at 4 time points (the first and the final weeks of RT, and 4 and 12 weeks afterward). The primary outcome was nutritional status at the end of RT as measured by the Patient-Generated Subjective Global Assessment. Results: Patients who received the EAT intervention had significantly better scores on the primary outcome of nutritional status at the critical end-of-treatment time point (β = −1.53 [−2.93 to −.13], P =.03). Intervention patients were also significantly more likely than control patients to be assessed as well-nourished at each time point, lose a smaller percentage of weight, have fewer treatment interruptions, present lower depression scores, and report a higher quality of life. Although results were not statistically significant, patients who received the intervention had fewer and shorter unplanned hospital admissions. Conclusions: This trial is the first of its kind to demonstrate the effectiveness of a psychological intervention to improve nutrition in patients with HNC who are receiving RT. The intervention provides a means to ameliorate malnutrition and the important related outcomes and consequently should be incorporated into standard care for patients receiving RT for HNC